languages Article Hesitations in Primary Progressive Aphasia Lorraine Baqué 1, * and María Jesús Machuca 2, * 1 SGR Laboratori fLexSem, Department of French and Romance Languages, Autonomous University of Barcelona, 08193 Cerdanyola del Vallès, Spain 2 SGR Transmedia Catalonia, Department of Spanish Studies, Autonomous University of Barcelona, 08193 Cerdanyola del Vallès, Spain * Correspondence: lorraine.baque@uab.cat (L.B.); mariajesus.machuca@uab.cat (M.J.M.) Abstract: Hesitations are often used by speakers in spontaneous speech not only to organise and prepare their speech but also to address any obstacles that may arise during delivery. Given the relationship between hesitation phenomena and motor and/or cognitive–linguistic control deficits, characterising the form of hesitation could be potentially useful in diagnosing specific speech and language disorders, such as primary progressive aphasia (PPA). This work aims to analyse the features of hesitations in patients with PPA compared to healthy speakers, with hesitations understood here as those related to speech planning, that is, silent or empty pauses, filled pauses, and lengthened syllables. Forty-three adults took part in this experiment, of whom thirty-two suffered from some form of PPA: thirteen from logopenic PPA (lvPPA), ten from nonfluent PPA (nfvPPA), and nine from semantic PPA (svPPA). The remaining 11 were healthy speakers who served as a control group. An analysis of audio data recorded when participants produced spontaneous speech for a picture description task showed that the frequency of silent pauses, especially those classified as long (>1000 ms) was particularly useful to distinguish PPA participants from healthy controls and also to differentiate among PPA types. This was also true, albeit to a lesser extent, of the frequency of filled pauses and lengthened syllables. Keywords: fillers; hesitations; pauses; primary progressive aphasia (PPA) Citation: Baqué, Lorraine, and María Jesús Machuca. 2023. Hesitations in 1. Introduction Primary Progressive Aphasia. When speakers take part in spontaneous oral communication, they rarely prepare Languages 8: 45. https://doi.org/ what they intend to say in advance but instead attempt to organise their speech while in 10.3390/languages8010045 the process of producing it. This organisation process is manifested in the frequent pausing that occurs in spontaneous speech, in all languages. However, pausing gives speakers Academic Editors: Jürgen Trouvain and Bernd Möbius time not only to organise but also to cope with the challenges involved with language processing, such as lexical retrieval, grammatical and phonological encoding, and control Received: 29 October 2022 and correction of what they are saying or have just said. Revised: 19 January 2023 While hesitation phenomena vary among individuals and are thus one way in which Accepted: 22 January 2023 individual styles of spontaneous speech can be distinguished (Maclay and Osgood 1959; Published: 1 February 2023 McDougall and Duckworth 2017; Llisterri et al. 2022), they are also linked to motor control and/or cognitive–linguistic deficits and therefore could potentially be useful in differen- tiating among specific speech and language disorders (Yunusova et al. 2016). This study aims to analyse pausing in the spontaneous speech of patients with primary progressive Copyright: © 2023 by the authors. aphasia (PPA), a degenerative disease that is characterised by progressive difficulty in Licensee MDPI, Basel, Switzerland. This article is an open access article speech and language functions due to frontotemporal lobar degeneration (Mesulam 2001; distributed under the terms and Gorno-Tempini et al. 2011). conditions of the Creative Commons 1.1. Hesitations Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ The term ‘hesitations’ refers to a set of phenomena that disrupt the flow of spoken 4.0/). language and are assumed not to be semantically relevant to the message conveyed, such as: Languages 2023, 8, 45. https://doi.org/10.3390/languages8010045 https://www.mdpi.com/journal/languages Languages 2023, 8, 45 2 of 44 • Repeats, which are meaningless repetitions of a syllable, word, or sequence of words; • False starts, which are incomplete or self-interrupted utterances; • Self-corrections, which consist of a word or a sequence of words intended to serve as a replacement for the immediately preceding utterance, which has been identified as an error by the speaker; • Lexical fillers, which are fixed expressions essentially devoid of real semantic content; • Hesitation pauses, which are pauses not due to articulatory or grammatical constraints (i.e., they are not juncture pauses). In this study, we will focus on the latter. Hesitation pauses include: • Silent pauses (also called ‘empty pauses’, ‘unfilled pauses’, or ‘silences’), which can be defined as a segment of time without speech but possibly with an inhalation noise; • Filled pauses (also known as ‘sound-filled vocalisations’ or ‘fillers’), which are vocali- sations that are not part of a lexical unit and that take some conventionalised form in a specific language (e.g., English: ‘um’/’uh’; Spanish: ‘e’); • Lengthenings, which consist of a sizeable non-phonemic prolongation of a phoneme or syllable of a word. As we have noted, hesitations—especially hesitation pauses—are assumed to appear when the speaker needs time to plan or encode his/her speech and can also be linked to difficulties in syntactic processing or lexical retrieval, as well as articulatory impairments (e.g., Maclay and Osgood 1959; Shriberg 1994; Ballard et al. 2014; Galluzzi et al. 2015). Hesitations also occur when speakers are monitoring their own inner or overt speech (Postma 2000) and in the process detect an error. That is why hesitations, in particular filled pauses and repetitions, not only appear during post-articulatory self-corrections but also signal pre-articulatory repairs. Finally, hesitations have been suggested to play a role in the management of verbal interaction. Thus, pauses—whether silent, filled, or consist- ing of lengthened syllables—indicate to an interlocutor that the speaker is relinquishing the floor (Cestero 2000). However, interaction is not necessary for hesitations to appear since these phenomena also occur when the speakers know they will not be interrupted (Machuca et al. 2015). Research on hesitations has raised methodological issues. The first issue is related to the classification of hesitation phenomena, which has been considered according to different criteria, leading to a certain amount of confusion over terminology. For instance, in the earliest attempt to classify hesitations, Maclay and Osgood (1959) identified four main types of hesitations, namely ‘repeats’, ‘false starts’ (which also include ‘self-corrections’), ‘filled pauses’, and ‘unfilled pauses’ (which include silent pauses and lengthenings). By contrast, Rose (2013) came up with seven categories, not four: ‘silent pauses’, ‘filled pauses’, ‘repairs’ (which correspond to the abovementioned ‘self-corrections’), ‘repeats’, ‘false starts’, ‘lengthenings’, and ‘lexical fillers’. Other researchers have regarded lengthenings and filled pauses as a single category, arguing that they perform the same function in oral discourse (Rebollo 1997). The counterargument is that these two phenomena should be analysed separately because the sound produced during filled pauses is unrelated to any specific lexical unit, while the elongated sound in lengthenings is the phoneme of a word (Blondet 2001; Machuca et al. 2015). Attempts have also been made to classify hesitations according to their duration. For example, Vasilescu and Adda-Decker (2007) compared the duration of intra-lexical lengthened vowels and filled pauses in three languages and found that while the mean duration of lengthened vowels was around 60 ms, with nearly 90% of them shorter than 150 ms, filled pauses ranged from 150 to 250 ms, and only 15% lasted less than 150 ms. With regard to silent pauses, Campione and Véronis (2002) analysed 6000 silent pauses in spontaneous speech in five different languages and concluded that they could be categorised as either short (<200 ms), medium (200–1000 ms), or long (>1000 ms) pauses. Most medium silences were associated with demarcative prosodic functions, whereas short silences were not linked to prosodic–syntactic boundaries, and long silences were only observed in spontaneous speech. Languages 2023, 8, 45 3 of 44 A second methodological issue (already pointed out by Maclay and Osgood in 1959) concerns the fact that the labelling of hesitation phenomena is often an ‘after-the-fact interpretation’ based on the listener’s judgement, since no discriminating threshold has been identified to distinguish, for example, between hesitation pauses on the one hand and silent pauses associated with other linguistic and expressive functions (Rodríguez Bravo 2022) on the other, or between lengthened syllables indicating hesitation and lengthened syllables attributable to other factors. Similarly, in spontaneous speech, the function being performed by a particular hesitation—whether it is allowing time for the speaker to plan, encode, or retrieve, or to monitor their inner speech, and so on—can only be hypothesised on an intuitive basis, allowing only tenuous conclusions to be drawn. Therefore, it is important to clarify that although in the title of this study we refer to ‘hesitation’, we will be focusing specifically on silent pauses, filled pauses, and lengthened syllables, though we will refer to all three phenomena as ‘pausing’, regardless of their length or function. 1.2. Primary Progressive Aphasia Primary progressive aphasia (PPA) is a degenerative neurological disease that causes speech and language dysfunction (Botha et al. 2015). Any examination of pausing patterns in patients with PPA requires first an understanding of the different types of PPA and their consequences with regard to language. It must first be emphasised that these different types or syndromes are characterised by clusters of features that do not necessarily constitute cleanly separated categories. In other words, a patient may be classified as having one type on the basis of a single feature pertaining to that type, whereas another patient may simultaneously show features of several types (Gorno-Tempini et al. 2011). That said, the three variants of PPA syndromes that have been distinguished are semantic PPA (svPPA), logopenic PPA (lvPPA), and nonfluent (or agrammatic) PPA (nfvPPA). People with svPPA differ very little from healthy speakers except in their lexical deficits. Their speech usually seems vague, with frequent word substitutions and other semantic paraphasias (Mesulam et al. 2014). Because sufferers of svPPA have difficulty accessing the words they need, they often resort to silent or filled pauses (Botha et al. 2015). They do not present phonological difficulties; rather, they exhibit a specific lexical–semantic deficit, which results in low values on the semantic depth index (SDI) (Quaranta et al. 2022). The SDI value corresponds to the degree of generality vs. specificity of a word and is calculated on the basis of a hierarchical semantic taxonomy of the complete lexicon of a language. For example, a very general term, such as ‘animal’, is relatively low on this hierarchy and a more specific term, such as ‘cat’ (a subcategory of ‘animal’), is higher. The SDI is a number indicating the degrees that separate a word from the most general root term that encompasses it. Thus ‘entity’ has an SDI of 1, ‘organism’ has an SDI of 2, ‘animal’ an SDI of 3, and so on, until we reach ‘cat’, with an SDI of 10. Therefore, lower SDI values are observed in speakers who have difficulty expressing themselves with precision, such as individuals with svPPA. As for lvPPA, its main feature is difficulty in lexical retrieval both in spontaneous speech and in naming tasks, as well as in repeating sentences (Gorno-Tempini et al. 2011; Giannini et al. 2017). Although their fluency is often considered normal and people with lvPPA can produce words with higher SDI values than people with svPPA, their speech rate is slow, and they often pause as they grasp for words. Phonological paraphasias related to phonemic confusion often occur due to the effort they expend in finding the words they need (Pérez Lancho and García Bercianos 2020). Contrary to what happens in apraxia of speech (see below), such phonological confusions are not due to a motor deficit. Some researchers have also shown that the language dysfunction involved in lvPPA is not limited to impairments in word retrieval and verbal working memory but also affects syntactic production, phonological encoding, and semantic representations (Teichmann et al. 2013; Staiger et al. 2021). Languages 2023, 8, 45 4 of 44 Finally, nfvPPA presents motor speech disorders as its main characteristic. Patients may show pronounced agrammatism. They usually suffer from apraxia of speech and present a slower speech rate than patients with the other two PPA variants. They use more hesitations and false starts, probably due to motor problems (Gorno-Tempini et al. 2011; Wilson et al. 2010). In addition, they show phonological problems such as elisions, substitutions, and additions of phonemes. Overall, they find it very challenging to produce spontaneous speech. Considering the abovementioned differences between the three main variants of PPA, it has been suggested that hesitation patterns in spontaneous speech might be of use in distinguishing among the three when it comes to diagnosis (Ash et al. 2013; Ballard et al. 2014; Poole et al. 2017; Potagas et al. 2022). 1.3. Hesitations in PPA Most research in aphasiology has focused on single-word production. Nevertheless, it has been suggested that spontaneous speech—in other words, speech that is neither pre-planned nor read nor limited to single words, also known as ‘continuous’ or ‘connected’ speech—offers novel possibilities for the diagnosis of PPA (Quaranta et al. 2022). In fact, research on spontaneous speech is particularly relevant for our purpose given that some hesitation phenomena appear only in this type of speech (Boschi et al. 2017). It is worth noting, however, that some of these studies do not specify what kinds of hesitations were included (see the methodological issues noted above). In addition, only a few studies have focused on hesitations in connection with PPA, mostly concluding that atypical hesitation patterns in general are common in PPA patients compared to control speakers. For example, Sajjadi et al. (2012) analysed spontaneous speech elicited in two different tasks and found that the frequency of hesitations was one of the parameters that differentiated nfvPPA participants (more than 10% of utterances), healthy speakers (less than 5%), and a group of PPA participants whose characteristics did not neatly fit into any of the three PPA subclasses (‘mixed PPA group’, less than 10% but more than 5%). Silent pauses are also useful for differentiating PPA types, though consensus has yet to be reached on which parameter—pause duration, frequency, or both—best distinguishes these patients. For example, Thomas (2021) indicated that the highest proportion of pauses were longer than 1000 ms for nonfluent aphasic speakers, while it was below 250 ms for fluent aphasic speakers. By contrast, after analysing 21 parameters associated with speech and pausing in Spanish, Baqué et al. (2022) concluded that the number of silences best discriminates among the different variants of PPA, rather than their duration. Similar results were found for Alzheimer’s disease, a pathology that is commonly associated with some PPA variants, especially lvPPA (Rohrer et al. 2012). Patients with Alzheimer’s also have difficulty recalling words or finding the right vocabulary to express themselves, and in one study it was again the frequency of pauses, not their duration, that distinguished healthy controls from Alzheimer’s patients (Lofgren and Hinzen 2022). By contrast, Potagas et al. (2022) found that both parameters, frequency and duration, could be used as comple- mentary biomarkers to discriminate between PPA patients and healthy speakers and also to differentiate the three variants of the illness. Finally, it has also long been noted that pauses in conversation are more frequent and longer in patients with post-stroke aphasia—a set of disorders that share some commonalities with PPA (Budd et al. 2010)—than in healthy speakers (Schlenck et al. 1987). Concerning filled pauses (or fillers), Christenfeld and Creager (1996) found them to be more frequent in nonfluent than in fluent post-stroke aphasia (0.9/min in Wernicke’s aphasia vs. 6.7/min in Broca’s aphasia). These authors also observed that the number of filled pauses per every hundred words rather than per minute better differentiates these two types of aphasia. As for syllable lengthening, though a study looking at overall syllable length in spontaneous speech found no differences between PPA patients and healthy speakers Languages 2023, 8, 45 5 of 44 (Code et al. 2013), to the best of our knowledge, no research has specifically addressed the question of lengthening as a hesitation strategy per se. In an attempt to shed further light on the relationship between silent pauses, filled pauses, and lengthened syllables and aphasia, we will analyse a wide range of param- eters related to the duration and frequency of these three types of hesitation pauses in spontaneous speech obtained from participants with PPA and matching controls. 1.4. Aims of the Current Study The aim of this study is to determine if three sorts of hesitation pauses—silent pauses, filled pauses, and lengthened syllables—can serve in any way to differentiate the main vari- ants of PPA, namely lvPPA, nfvPPA, and svPPA, in terms of atypicality and (dis)similarity. Thus, the main objective of this study is to answer the following questions: 1. Atypicality: 1.1 Are the pausing patterns of the three main variants of PPA atypical as com- pared to control speakers of a similar age? 1.2 If so, what are the parameters related to pausing that characterise the atypical- ity of each variant? 1.3 How does all that contribute to a better understanding of the underlying deficits and allow us to characterise each variant in terms of (dys)fluency? 2. (Dis)similarity: 2.1 To what extent are the observed abnormal pausing patterns (dis)similar in the three main variants of PPA? 2.2 If so, what are the parameters related to pausing that differentiate each group from the other two? 2.3 How does all that contribute to a better understanding of the deficit-specific vs. transversal nature of the impairment in each variant? 3. Parameter relevance: 3.1 What are the parameters related to pausing that best explain the atypicality of each variant and the (dis)similarity between them? 2. Materials and Methods 2.1. Participants Participants were recruited from a cohort of patients with PPA in the Memory Unit of Sant Pau Hospital in Barcelona between September 2019 and March 2022. The diag- nosis of PPA was established following international criteria (Gorno-Tempini et al. 2011). Patients were administered a standardised speech assessment (Table 1) as well as neu- ropsychological and neurological evaluations, neuroimaging (magnetic resonance imaging or computed tomography), and neurodegeneration biomarkers in cerebrospinal fluid in accordance with the Memory Unit’s usual procedures (Alcolea et al. 2019). Based on the results, 32 participants were classified as suffering from one of the following vari- ants: logopenic (lvPPA, n = 13), nonfluent (nfvPPA, n = 10), and semantic (svPPA, n = 9). The severity of their disease was estimated by means of their scores on the Spanish- language versions of two tests, the Mini-Mental State Examination (MMSE, Blesa et al. 2001) and the Clinical Dementia Rating–FTLD scale modified (CDR-FTLD, Knopman et al. 2008). No significant differences were found between the three groups (MMSE scores: lvPPA = 25.92 ± 3.35, nfvPPA = 25.80 ± 3.76, svPPA = 23.22 ± 4.05, p = 0.206; CDR-FTLD scores: lvPPA = 0.53 ± 3.3, nfvPPA = 0.50 ± 3.7, svPPA = 0.77 ± 4.0, p = 0.154). The average age of participants was similar in the three groups (71.78 ± 4.6, 72.81 ± 10.2 and 74.88 ± 3.3). Eleven healthy individuals with no neurological conditions or disorders were recruited at the Memory Unit of the same hospital to serve as a control group. Their average age was 73.18 (±3.8). No significant differences were found for age (p = 0.7). All the participants were native speakers of Spanish or native Catalan–Spanish bilinguals.1 Languages 2023, 8, 45 6 of 44 Demographic information about the participants for each PPA variant and controls is provided in Table 1. Table 1. Demographic information of the participants. 1 Controls lvPPA nfvPPA svPPA (n = 11) (n = 13) (n = 10) (n = 9) Female 6 (54.5%) 6 (46.2%) 6 (60%) 5 (55.6%) Sex Male 5 (45.5%) 7 (53.8%) 4 (40%) 4 (44.4%) Right 11 (100%) 10 (76.9%) 10 (100%) 8 (88.90%) Demographic data Dominant hand Left 1 (7.7%) Both 2 (15.4%) 1 (11.10%) Age 73.18 (3.8) 71.78 (4.6) 72.81 (10.2) 74.88 (3.3) CDR-FTLD (0–21, lower scores = Neurological test 0.00 (0.00) 4.96 (2.14) 3.35 (2.19) 5.50 (3.28) less impairment) results MMSE (/30) 29.18 (0.40) 25.92 (3.35) 25.80 (3.76) 23.22 (4.05) Spontaneous BNT (/60) 51.27 (3.87) 30.76 (10.31) 44.10 (11.44) 44.10 (13.16) Sentence comprehension (/15) 14.90 (0.3) 13.53 (2.5) 13.40 (2.0) 13.44 (2.2) Language (BDAE) Phonetic fluency (in 60 s) 16.81 (1.47) 8.76 (4.76) 5.4 (3.83) 8.55 (5.43) Semantic fluency (in 60 s) 16.9 (2.77) 8.61 (3.37) 10.3 (4.76) 7.77 (3.41) WAIS Digit Span forward (/9) 6.54 (1.0) 4.69 (1.3) 4.40 (0.8) 5.22 (1.2) WAIS Digit Span backwards (/9) 5.36 (0.9) 3.30 (1.0) 3.10 (0.8) 3.77 (0.9) Executive Functions TMT-A 42.54 (9.2) 123.07 (177.47) 77.20 (51.39) 71.44 (48.9) TMT-B 85.00 (28.5) 426.23 (399.3) 328.00 (260.6) 388.22 (323.3) Visual space Poppelreuter Test × 2 (/5) 5 (0) 4.53 (0.77) 4.9 (0.31) 4.33 (0.70) recognition tasks CERAD, copy (/11) 7.36 (1.62) 6.38 (1.5) 5.40 (1.17) 4.44 (1.13) FCSRT immediate recall (/48) 39.36 (4.4) 21.46 (11.3) 36.50 (10.6) 13.44 (11.0) Memory FCSRT delayed recall (/16) 14.36 (1.6) 8.3 (5.0) 12.70 (4.4) 4.55 (4.1) CERAD, recall (/11) 5.36 (2.24) 2.0 (2.27) 2.70 (1.33) 1.55 (1.87) 1 BDAE: Boston Diagnostic Aphasia Examination Test (Spanish-language version, García-Albea et al. 1996a); BNT: Boston Naming Test (Spanish-language version, García-Albea et al. 1996b); CDR-FTLD: Clinical Dementia Rating–FTLD scale-modified (Knopman et al. 2008); CERAD: Consortium to Establish a Registry for Alzheimer’s Disease (Morris et al. 1988); FCSRT: Free and Cued Selective Reminding Test (Grober and Buschke 1987); lvPPA: logopenic variant of primary progressive aphasia; MMSE: Mini-Mental State Examination (Blesa et al. 2001); nfvPPA: nonfluent variant of primary progressive aphasia; Poppelreuter Test: Poppelreuter-Ghent Overlapping Figures Test (Ghent 1956; Poppelreuter 1917); svPPA: semantic variant of primary progressive aphasia; TMT: Trail-Making Test (Reitan 1955); WAIS Digit Span: Wechsler Adult Intelligence Scale Digit Span (Wechsler 2008). 2.2. Speech Assessment For speech evaluation, a Spanish-language version of the SpeechFTLD protocol was used (Vogel 2018). Designed to sample speech, the protocol consists of various tasks (a balanced text, repetition of sentences and words, counting numbers, and so on), which have different levels of complexity. These tasks were administered to participants as part of a clinical trial during initial evaluation sessions. In the task intended to elicit spontaneous speech for analysis in this study, participants were asked to describe what they saw in a picture showing a picnic scene based on Kertesz (2006). The examiner did not intervene unless the participant’s description was too short to provide a language sample adequate for analysis. In such cases, the examiner attempted to prompt the participant to elaborate with questions such as ‘What else can you see in the picture?’. 2.3. Speech Samples A health professional audio-recorded each participant performing the picnic scene description in a single session in an office at the Sant Pau Hospital using an application designed by Redenlab for the iPad (https://redenlab.com, accessed on 1 September 2022), with a Lavalier microphone designed for iPhone and iPad (https://apogeedigital.com/ products/clipmic-digital, accessed on 1 September 2022). Languages 2023, 8, 45 7 of 44 Recordings were automatically segmented and annotated into speech and silence seg- ments using Praat’s Sound: To TextGrid (silences) command (Boersma and Weenink 2020). Speech samples were then manually transcribed orthographically. The intervention of the health professional was neither transcribed nor further analysed, and pauses preceding and following the intervention were removed from any further analysis, as they could not be attributed with any certainty to the participant’s speech organisation. Based on the orthographic transcription, each recording was automatically transcribed phonetically and aligned with sound using EasyAlign (Goldman and Schwab 2014). The resulting alignment in phones, syllables, and words was manually corrected. Finally, filled pauses and lengthened syllables were also manually labelled. From the annotated speech samples, we extracted 48 parameters related to hesitation. For each type of pause (silent pauses, filled pauses, and lengthened syllables), we computed 9 parameters: (1) mean duration; (2) median duration; (3) standard deviation of the duration; (4) number of each type of pause and all pauses together per (a) second of speech, (b) second of total duration (speech + pauses), (c) total number of syllables, and (d) total number of words; and (5) proportion of pause time over (a) the total duration of speech, and (b) the total duration (speech + pauses). Additionally, we classified every silent pause as long, medium, or short, according to Campione and Véronis (2002) criteria and calculated the percentage of each type of pause (long, medium, and short) over the total number of silent pauses. Then, for each of these three silent pause length categories, we also computed the number of pauses per (a) second of speech, (b) second of total duration (speech + pauses), (c) total number of syllables, and (d) total number of words. Table 2 lists these variables in the order in which they have been described here. A detailed list of the 48 variables, ordered orthographically, can be found in Appendix A, Table A1. Table 2. Description of acoustic parameters. Type of Parameters Description Parameters Mn_DurPsil Mean (Mn_), median (Mdn_), and standard deviation (SD_) of Mn_DurPfill the duration (Dur) of: Mn_DurSlbLONG Mdn_DurPsil Pause duration - Silent pauses (Psil); Mdn_DurPfill - Filled pauses (Pfill); Mdn_DurSlbLONG - Lengthened syllables (SlbLONG). SD_DurPsil SD_DurPfill SD_DurSlbLONG Ratio of the number (R_Num_) of: Distribution of long, - Long silent pauses (LongPsil); R_NumLongPsil_NumTotPsil medium, and short - Medium silent pauses (MediumPsil); R_NumMediumPSil_NumTotPsil silent pauses - Short silent pauses (ShortPsil); R_NumShortPsil_NumTotPsil relative to the total number of silent pauses (_NumTotPsil) Number (Num) of NumLongPsil_DurSpeech - Silent pauses: NumMediumPsil_DurSpeech ◦ Long silent pauses (LongPsil); NumShortPsil_DurSpeech ◦ Medium silent pauses (MediumPsil); NumPsil_DurSpeech ◦ Short silent pauses (ShortPsil); NumPfill_DurSpeech ◦ All silent pauses: long + medium + short (Psil). NumSlbLONG_DurSpeech Pause frequency per - Filled pauses (Pfill); NumPausesALL_DurSpeech time unit - Lengthened syllables (SlbLONG); NumLongPsil_DurTot - All pauses: silent + filled + lengthened syllables NumMediumPsil_DurTot (PausesALL); NumShortPsil_DurTot NumPsil_DurTot per: NumPfill_DurTot - Second of speech (_DurSpeech); NumSlbLONG_DurTot - Total duration (_DurTot). NumPausesALL_DurTot Languages 2023, 8, 45 8 of 44 Table 2. Cont. Type of Parameters Description Parameters Number (Num) of NumLongPsil_NumTotSlb - Silent pauses: NumMediumPsil_NumTotSlb ◦ Long silent pauses (LongPsil); NumShortPsil_NumTotSlb ◦ Medium silent pauses (MediumPsil); NumPsil_NumTotSlb ◦ Short silent pauses (ShortPsil); NumPfill_NumTotSlb ◦ All silent pauses: long + medium + short (Psil). NumSlbLONG_NumTotSlb Pause frequency per - Filled pauses (Pfill); NumPausesALL_NumTotSlb linguistic unit - Lengthened syllables (SlbLONG); NumLongPsil_NumTotWords - All pauses: silent + filled + lengthened syllables NumMediumPsil_NumTotWords (PausesALL); NumShortPsil_NumTotWords NumPsil_NumTotWords per: NumPfill_ NumTotWords - Syllable (_NumTotSlb); NumSlbLONG_NumTotWords - Word (_NumTotWords). NumPausesALL_NumTotWords Ratio of the duration (R_Dur) of - Silent pauses (Psil); R_DurPsil_DurSpeech - Filled pauses (Pfill); R_DurPfill_DurSpeech - Lengthened syllables (SlbLONG); R_DurSlbLONG_DurSpeech - All pauses: silent + filled + lengthened syllables R_DurPausesALL_DurSpeech Pause duration ratio (PausesALL); R_DurPsil_DurTot per: R_DurPfill_DurTot R_DurSlbLONG_DurTot - Second of speech (_DurSpeech); R_DurPausesALL_DurTot - Second of total duration (_DurTot); Such a wide range of parameters should make it possible to account for the use of different types of pauses by each group of participants. Pause duration, variability, and frequency are assumed to reflect specific difficulties in speech processing (see above, Section 1), related to both speech–motor and cognitive–linguistic levels. Distinguishing between the frequency of pauses per word and per syllable should allow us to infer whether such difficulties arise from articulatory planning or execution deficits (increased frequency of pauses both per syllable and per word) or from lexical retrieval impairments (increased frequency per word, but not per syllable). Although pause–speech and pause–total duration ratios co-vary, we decided to include both parameters to allow comparisons with previous studies (see below, Discussion). 2.4. Statistical Analysis Different statistical analyses were carried out to observe which parameters would vary as a function of the group and discern patterns and trends in the behaviour of each PPA group compared to the healthy control group. First, linear mixed-effects models were used in order to check for effects within and between groups. The duration was analysed as a function of group (four levels: control, lvPPA, nfvPPA, svPPA) and pause type (three levels: silent pauses, filled pauses, lengthened syllables), with speaker entered as a random factor, in R (v. 4.2.0, R Core Team 2022). The reference group was the group of healthy speakers. Then, linear regression models were used to estimate how the dependent variables (all the parameters in Table 2) changed as a function of the groups considered. The atypicality of each group of participants with PPA was determined by comparing each patient group with the healthy group. An analysis of the (dis)similarity among groups of participants with PPA was achieved by contrasting these three groups after excluding data from the control group. Languages 2023, 8, 45 9 of 44 3. Results The results of this study are structured in five subsections, depending on the type of parameters considered, namely: 1. Pause duration: mean (raw data), median, and standard deviation; 2. Distribution of long, medium, and short silent pauses; 3. Pause frequency: number of pauses per second of speech and per total duration; 4. Pause frequency: number of pauses per syllable and per word; 5. Pause–speech and pause–total duration ratios. For every parameter, we carried out two different analyses corresponding to the following two goals: 1. Atypicality: to account for any atypicality found in PPA by means of linear regression models in which each group of participants with PPA was compared to the control group; 2. (Dis)similarity: to determine whether the parameter would serve to differentiate any one of the three PPA groups from the other two by means of linear regression models where data corresponding to controls were excluded. 3.1. Pause Duration: Mean (Raw Data), Standard Deviation, and Median As can be seen in Table 3, overall, the mean duration of silent pauses was shorter in controls (0.604 s) than in each of the patient groups (svPPA = 0.769 s; lvPPA = 0.837 s, and especially nfvPPA = 1.377 s). As for filled pauses and lengthened syllables, lvPPA participants presented similar duration values to controls (filled pauses: 0.622 s vs. 0.606 s; lengthened syllables: 0.589 s vs. 0.585 s, respectively), whereas the mean duration was longer in the nfvPPA group (0.674 s and 0.656 s) and shorter in the svPPA group (0.489 s and 0.520 s, respectively). Table 3. Mean and standard deviation values for the duration of each pause type (silent pause, filled pause, or lengthened syllable), by group. Parameter Control lvPPA nfvPPA svPPA N Control N Mean (sd) N Mean (sd) N Mean (sd) Dur_Psil 696 0.604 (0.735) 778 0.837 (0.890) 283 1.377 (2.626) 200 0.769 (0.839) Dur_Pfill 126 0.606 (0.429) 161 0.622 (0.387) 41 0.674 (0.320) 20 0.489 (0.239) Dur_SlbLONG 290 0.585 (0.179) 247 0.589 (0.259) 85 0.656 (0.285) 78 0.520 (0.156) The standard deviation of the duration of silent pauses showed a lower variabil- ity in controls (0.735 s) than in each group of persons with PPA (in ascending order, svPPA = 0.839 s, lvPPA = 0.890, and nfvPPA = 2.626 s). On the other hand, controls were associated with the highest standard deviation values of filled pause duration (0.429 s vs. lvPPA = 0.387 s, nfvPPA = 0.320 s, and svPPA = 0.239 s). As for lengthened syllables, the lowest standard deviation value corresponded to the svPPA group (0.156 s), followed by controls (0.179 s), the lvPPA group (0.259 s), and the nfvPPA group (0.285 s). Overall, the median duration (see Table 4) of silent pauses was shorter in controls (0.503 s) than in each of the PPA groups (svPPA = 0.663 s; lvPPA = 0.678 s, and nfvPPA = 794 s). As for filled pauses, the lowest value corresponded to the svPPA group (0.427 s), followed by controls (0.524 s), the nfvPPA group (0.535 s), and the lvPPA group (0.579 s). The median duration of lengthened syllables was shorter in the lvPPA group (0.502 s) than in the controls (0.537 s), the lvPPA group (0.559 s), or the nfvPPA group (0.616 s). Languages 2023, 8, 45 10 of 44 Table 4. Mean and standard deviation values for the median duration of each pause type, by group. Parameter Control lvPPA nfvPPA svPPA N Control N Mean (sd) N Mean (sd) N Mean (sd) Mdn_DurPsil 696 0.503 (0.169) 778 0.678 (0.193) 283 0.794 (0.472) 200 0.663 (0.432) Mdn_DurPfill 126 0.524 (0.183) 161 0.579 (0.212) 41 0.535 (0.289) 20 0.427 (0.216) Mdn_DurSlbLONG 290 0.537 (0.069) 247 0.559 (0.128) 85 0.616 (0.121) 78 0.502 (0.089) 3.1.1. Atypicality of Each PPA Group In order to find out the extent to which pause duration was atypical in each of the PPA groups, we compared each patient group to the control group. Nine separate models were computed: one for each pause type (silent pauses, filled pauses, lengthened syllables) and PPA group (lvPPA vs. controls, nfvPPA vs. controls, and svPPA vs. controls). The estimates are reported in Appendix A, Table A2. With regard to standard deviation and median values, linear regression models were carried out for each PPA group (lvPPA vs. controls, nfvPPA vs. controls, and svPPA vs. controls). The estimates are reported in Appendix A, Tables A3 and A4, respectively. In lvPPA–controls comparisons, the results show no significant effect of group on the duration of any type of pause. Although the mean duration of silent pauses was longer in the lvPPA group than in controls (0.837 s vs. 0.604 s), this difference did not reach significance (p = 0.050). Compared to controls, the nfvPPA group presented significantly longer silent pauses (1.377 s vs. 0.604 s; p = 0.047) and lengthened syllable duration (0.656 s vs. 0.585 s; p = 0.025). Concerning the svPPA group, they presented shorter lengthened syllables than con- trols (0.520 s vs. 0.585 s; p = 0.033). No other significant effects were observed. No significant differences in the duration of filled pauses were found for any of the PPA groups compared to controls. The comparisons of the standard deviation of pause duration between the lvPPA group and controls showed no significant effect of group for any of the pause types considered. By contrast, compared to controls, the nfvPPA group was associated with lower standard deviation values of filled pause duration (0.320 s vs. 0.429 s) but higher values in those of lengthened syllables (0.285 s vs. 0.179 s). The standard deviation of silent pause duration was greater in the nfvPPA group than in the control group (2.626 s vs. 0.735 s), but this difference did not reach significance (p = 0.082). As for the svPPA group, they differed from controls only in their shorter standard deviation of lengthened syllables (0.156 s vs. 0.179 s). Concerning the median duration, we observed a significant difference between the lvPPA group and controls for silent pauses, the former being associated with much higher values (0.678 s vs. 0.503 s). No significant effects were found for either filled pauses or lengthened syllables. Neither in the nfvPPA group nor in the svPPA group was there any significant effect of group on the median duration of any of the pause types considered. 3.1.2. (Dis)Similarity among PPA Groups To investigate whether pause duration served in any way to differentiate the three PPA groups, we excluded the data from the control group and computed mixed effects linear regression models. The estimates are reported in Appendix A, Table A5. Linear regression models were also calculated with the standard deviation and me- dian values of the duration of each type of pause (see Appendix A, Tables A6 and A7, respectively). No significant effect of group was found on the duration of silent pauses, filled pauses, or lengthened syllables. Therefore, despite sizeable differences between the mean values observed (see Table 3), none of these parameters alone allowed us to distinguish among the three PPA groups. Languages 2023, 8, 45 11 of 44 Concerning standard deviation values of pause duration, the results reveal a single significant group effect, which was related to lengthened syllables (p = 0.006). The post hoc analyses showed that the only significant contrast was between the nfvPPA and svPPA groups, with the former being associated with much higher variability (0.285 s vs. 0.156 s). As for median duration, no significant effect of group was found on silent pauses, filled pauses, or lengthened syllables. 3.2. Distribution of Short, Medium, and Long Silent Pauses Pause duration is extremely varied in spontaneous speech, and often presents tri- modal behaviour (Campione and Véronis 2002), making overall mean and median values of little interest. Therefore, we categorised silent pauses into three length types, following Campione and Véronis’ criteria, namely short (<0.2 s), medium (0.2–1.0 s), and long (>1 s). From the descriptive data for the proportion of short, medium, and long silent pauses shown in Table 5, one can see that the four groups used medium pauses more often than short or long ones. The mean proportion of long pauses was greater in the svPPA group (22.7%), the lvPPA group (28.1%), and especially the nfvPPA group (33.3%), than in controls (16.1%). On the other hand, the three PPA groups used short pauses less frequently than did controls (svPPA = 12.1%, nfvPPA = 12.6%, lvPPA = 13.4%, vs. controls = 22.0%). Table 5. Mean and standard deviation values of the proportion of the total number of silent pauses which are long, medium, or short, by group. Parameter Control (N = 11) lvPPA (N = 13) nfvPPA (N = 10) svPPA (N = 9) R_NumLongPsil_NumTotPsil 0.161 (0.115) 0.281 (0.151) 0.333 (0.234) 0.227 (0.221) R_NumMediumPsil_NumTotPsil 0.619 (0.111) 0.585 (0.146) 0.541 (0.175) 0.653 (0.178) R_NumShortPsil_NumTotPsil 0.220 (0.116) 0.134 (0.086) 0.126 (0.081) 0.121 (0.101) 3.2.1. Atypicality of Each PPA Group The ‘atypicality’ of each PPA group in the proportion of long, medium, and short silent pauses was assessed using linear regression models. The estimates of the results are reported in Appendix A, Table A8. The results show that the lvPPA group differed significantly from controls in that they took long silent pauses more often (28.1% vs. 16.1%; F(1) = 4.676, p = 0.042) and used short pauses less frequently (13.4% vs. 22.0%; F(1) = 4.407, p = 0.047). The effects observed in the nfvPPA group were similar (long: F(1) = 4.767, p = 0.042; short: F(1) = 4.604, p = 0.045), but even stronger: almost one-third of silent pauses exceeded 1 s, while only 12.6% were inferior to 0.2 s. As for the svPPA group, no significant differences were observed for any of the parameters considered. No significant differences were observed in the proportion of medium pauses for any of the PPA groups compared to controls. 3.2.2. (Dis)Similarity among PPA Groups In order to see whether the proportion of short, medium, or long silent pauses would allow us to differentiate the three PPA groups from each other, we carried out linear regression models in which group was entered as the independent variable. The results are reported in Appendix A, Table A9. No significant group effect was found for any of the proportions under consideration, showing that none of these parameters can be used alone to distinguish among the three variants of PPA. 3.3. Pause Frequency: Number of Pauses per Second Pause frequency, computed as the number of pauses produced per second, is believed to be atypical in PPA (see Section 1). We computed the pause frequency (per second of Languages 2023, 8, 45 12 of 44 speech and per second of total duration, including speech and pauses) for each participant in our study, separately for each pause type (silent pause, filled pause, and lengthened syllables), and together, adding the frequency of the three categories of pauses. As can be seen in Table 6, in the control group, on average, there were 0.941 pauses per second of speech (0.658 per second of total duration), distributed as follows: 0.593 silent pauses, 0.100 filled pauses, and 0.249 lengthened syllables (0.411 silent pauses, 0.070 filled pauses and 0.178 lengthened syllables per second of total duration, respectively). Table 6. Mean and standard deviation values of pause frequency (per second of speech/total duration), by pause type (Psil = silent pauses, Pfill = filled pauses, SlbLONG = lengthened syllables, PausesALL = all three together) and group. Control lvPPA nfvPPA svPPA Parameter (N = 11) (N = 13) (N = 10) (N = 9) NumPsil_DurSpeech 0.593 (0.152) 0.870 (0.235) 0.843 (0.258) 0.574 (0.141) NumPsil_DurTot 0.411 (0.091) 0.476 (0.113) 0.407 (0.126) 0.382 (0.084) NumPfill_DurSpeech 0.100 (0.047) 0.164 (0.149) 0.126 (0.143) 0.060 (0.053) NumPfill_DurTot 0.070 (0.031) 0.088 (0.076) 0.052 (0.035) 0.042 (0.042) NumSlbLONG_DurSpeech 0.249 (0.096) 0.280 (0.138) 0.242 (0.136) 0.209 (0.125) NumSlbLONG_DurTot 0.178 (0.074) 0.162 (0.092) 0.129 (0.087) 0.142 (0.089) NumPausesALL_DurSpeech 0.941 (0.194) 1.312 (0.329) 1.210 (0.388) 0.843 (0.224) NumPausesALL_DurTot 0.658 (0.125) 0.727 (0.183) 0.585 (0.208) 0.567 (0.164) For every parameter, the lvPPA group showed the highest mean values, with one exception, the number of lengthened syllables per second of total duration, which was slightly smaller than that of controls (0.162 vs. 0.178). On average, the lvPPA group produced 1.312 pauses per second of speech (0.727 per second of total duration): 0.870 silent pauses, 0.164 filled pauses, and 0.280 lengthened syllables (0.476, 0.088 and 0.162, respectively, per second of total duration). On the other hand, the lowest number of pauses taking into account only speech or total duration was observed in the svPPA group, either separately for silent pauses (0.574 and 0.382, respectively), filled pauses (0.060 and 0.042), and lengthened syllables (0.209 and 0.142), or when the three types of pauses were considered together (0.843 and 0.567, respectively). The only exception concerns the number of lengthened syllables per second of total duration, which was slightly higher than for the nfvPPA group. The results for the nfvPPA group are somewhere in between the two poles represented by the svPPA and lvPPA groups. The mean pause frequency observed in the nfvPPA group per second of speech was higher than that of all the other groups except lvPPA, either overall (1.210 pauses per second), or for silent (0.843) or filled (0.126) pauses. The number of lengthened syllables per second of speech (0.242) was similar to that recorded for controls. However, when pause frequency was computed on the total duration of speech and pauses, the values obtained were similar to or lower than those obtained for controls: the nfvPPA group produced fewer pauses overall (0.585/s), fewer filled pauses (0.052/s), fewer lengthened syllables (0.129/s, which was even lower than in the svPPA group) than controls, and almost the same number of silent pauses (0.407/s). Further analysis of the frequency of silent pauses per second of speech or per second of total duration, in which we distinguished short (<0.2 s), medium (0.2–1.0 s), and long (>1.0 s) pauses (see Table 7), showed that control participants had fewer long silent pauses per second of speech (0.094 vs., in increasing order, svPPA: 0.133, lvPPA: 0.232, and nfvPPA: 0.311 pauses/s) and more short silent pauses (0.136 vs., in descending order, lvPPA: 0.126, nfvPPA: 0.098, and svPPA: 0.065 pauses/s). Similar results were obtained for frequencies computed per second of total duration. Languages 2023, 8, 45 13 of 44 Table 7. Mean and standard deviation values of silent pause frequency (per second of speech/total duration), by length category and group. Control lvPPA nfvPPA svPPA Parameter (N = 11) (N = 13) (N = 10) (N = 9) NumLongPsil_DurSpeech 0.094 (0.073) 0.232 (0.112) 0.311 (0.291) 0.133 (0.121) NumLongPsil_DurTot 0.062 (0.041) 0.123 (0.053) 0.111 (0.052) 0.078 (0.056) NumMediumPsil_DurSpeech 0.363 (0.096) 0.511 (0.183) 0.433 (0.142) 0.377 (0.139) NumMediumPsil_DurTot 0.252 (0.061) 0.284 (0.110) 0.238 (0.133) 0.258 (0.096) NumShortPsil_DurSpeech 0.136 (0.090) 0.126 (0.088) 0.098 (0.053) 0.065 (0.044) NumShortPsil_DurTot 0.097 (0.065) 0.069 (0.052) 0.056 (0.043) 0.047 (0.035) As for medium silent pauses, the highest frequency per second of speech was found in the lvPPA group (0.511/s), followed by the nfvPPA group (0.433/s), the lvPPA group (0.377/s), and, finally, by controls (0.363/s). When computed by second of total duration, the highest value corresponded to the lvPPA group (0.284/s), followed by the svPPA group and controls (0.258 and 0.252/s). The lowest frequency of medium silent pauses per second of total duration was seen in the nfvPPA group (0.238/s). 3.3.1. Atypicality of Each PPA Group In order to describe the extent to which the abovementioned differences in the fre- quency of pauses between each PPA group and controls are attributable to specific ‘atyp- icalities’, we carried out linear regression models of the effect of group on each of the parameters. Separately models were computed for each parameter and group comparison (lvPPA vs. controls, nfvPPA vs. controls, and svPPA vs. controls). The obtained estimates are reported in Appendix A, Table A10. No significant effect of group was found for any of the comparisons of a PPA group with controls in terms of pause frequency per second of total duration, either when silent pauses, filled pauses, and lengthened syllables were considered separately, or when the three pause types were taken together. As for pause frequency per second of speech, the results show that the lvPPA group differed significantly from controls in the number of silent pauses (lvPPA = 0.870 vs. control = 0.593 pauses/s, p = 0.003), as well as in the number of overall pauses (lvPPA = 1.312 vs. control = 0.941 pauses/s, p = 0.003). Concerning the nfvPPA group, the frequency of silent pauses was also significantly higher than that of controls (nfvPPA = 0.843 vs. control = 0.593 pauses/s, p = 0.013). The number of overall pauses per second of speech was also greater in the nfvPPA group (1.210 vs. 0.941 pauses/s, respectively), but the difference was not significant (p = 0.055). No significant effect of group was found in lvPPA–controls comparisons for any of the parameters considered. In addition, more fine-grained analyses were conducted on long, medium, and short silent pauses taken separately (see Appendix A, Table A11). The results show that the lvPPA group differed significantly from controls only in the frequency of long silent pauses per second (of both speech and total duration) and of medium silent pauses per second of speech. In all these cases, the lvPPA group produced pauses more often than controls (0.232 vs. 0.094 long pauses/s of speech, p = 0.002; 0.123 vs. 0.062 long pauses/s of total duration, p = 0.005; 0.511 vs. 0.363 medium pauses/s of speech, p = 0.025). No significant effects were found for short pauses or for the number of medium pauses per second of total duration. The number of long pauses was also significantly higher in the nfvPPA group than in controls, both per second of speech (0.311 vs. 0.094 pauses/s, p = 0.027) and per second of total duration (0.111 vs. 0.062 pauses/s, p = 0.024). No further significant differences were found between the nfvPPA and svPPA groups. As for the svPPA participants, by contrast, they differed from controls only in the number of short silent pauses per second of speech, which was significantly lower (0.065 vs. Languages 2023, 8, 45 14 of 44 0.136/s, p = 0.046). The frequency of short silent pauses per second of total duration was also lower in the lvPPA group than in controls (0.047 vs. 0.097 pauses/s), but the difference did not reach significance (p = 0.056). 3.3.2. (Dis)Similarity among PPA Groups We carried out linear regression models of the effect of group on the frequency of silent and filled pauses, lengthened syllables, and all pauses taken together in order to determine the extent to which the three PPA groups might differ one from another in terms of each of these parameters (see Appendix A, Table A12). The results show no significant effects except for the number of silent pauses (p = 0.010) and of overall pauses (p = 0.008) per second of speech. In both cases, the post hoc analyses revealed a single significant contrast between the nfvPPA and svPPA groups (0.843 vs. 0.574 silent pauses/s, p = 0.0343; 1.210 vs. 0.843 overall pauses/s, p = 0.0512). Similar analyses were carried out for long, medium, and short silent pauses taken separately (see Appendix A, Table A13), but no significant effects were found for any of the parameters considered. Therefore, the frequency of silent pauses, divided by length type, did not allow us to differentiate among the three PPA groups. 3.4. Pause Frequency: Number of Pauses per Syllable/Word Pause frequency, computed as the number of pauses per syllable or word, has also been conjectured to be atypical in PPA. In our study (see Table 8), on average, there were 0.201 pauses per syllable (i.e., a pause every 4.8 syllables) and 0.345 pauses per word (i.e., a pause every 2.9 words) in the control group. These pauses were distributed as follows: 0.126 silent pauses, 0.022 filled pauses, and 0.053 lengthened syllables per syllable, and 0.216 silent pauses, 0.037 filled pauses, and 0.091 lengthened syllables per word. Table 8. Mean and standard deviation values of pause frequency (per syllable/word), by type and group. Control lvPPA nfvPPA svPPA Parameter (N = 11) (N = 13) (N = 10) (N = 9) NumPsil_NumTotSlb 0.126 (0.034) 0.193 (0.066) 0.210 (0.067) 0.108 (0.029) NumPsil_NumTotWords 0.216 (0.057) 0.298 (0.099) 0.357 (0.129) 0.172 (0.050) NumPfill_NumTotSlb 0.022 (0.011) 0.039 (0.042) 0.031 (0.031) 0.011 (0.010) NumPfill_NumTotWords 0.037 (0.018) 0.059 (0.061) 0.054 (0.056) 0.018 (0.016) NumSlbLONG_NumTotSlb 0.053 (0.021) 0.061 (0.030) 0.060 (0.037) 0.040 (0.023) NumSlbLONG_NumTotWords 0.091 (0.037) 0.094 (0.044) 0.100 (0.062) 0.063 (0.038) NumPausesALL_NumTotSlb 0.201 (0.048) 0.293 (0.106) 0.301 (0.102) 0.159 (0.044) NumPausesALL_NumTotWords 0.345 (0.080) 0.451 (0.151) 0.511 (0.191) 0.253 (0.076) The lowest values for frequency of pauses per syllable and per word were found in the svPPA group, for every type of pauses, and when all types were considered together. On average, the svPPA group produced 0.159 pauses/syllable or 0.253 pauses/word, which means a pause every 6.3 syllables or 4.0 words. On the other hand, the lvPPA and nfvPPA groups presented higher values than con- trols in each parameter considered. Overall, the lvPPA group produced 0.293 pauses/syllable and 0.451 pauses per word, that is, a pause every 3.4 syllables or 2.2 words. As for the nfvPPA group, there was a pause about every 3.3 syllables or 2.0 words. An exploration of the frequency of silent pauses per syllable and word, grouped by length type (see Table 9), showed that controls produced 0.020 long pauses per syllable (0.033 per word), which means a long pause every 50.0 syllables or 30.3 words. The frequency of long silent pauses was slightly higher in the svPPA group (a pause every 38.5 syllables or 24.4 words), and much higher in both the lvPPA group (a pause every 19.2 syllables or 12.5 words) and the nfvPPA group (one every 13.3 syllables and 7.7 words). Languages 2023, 8, 45 15 of 44 Table 9. Mean and standard deviation values of silent pause frequency (per syllable/word), by length category and group. Control lvPPA nfvPPA svPPA Parameter (N = 11) (N = 13) (N = 10) (N =9) NumLongPsil_NumTotSlb 0.020 (0.014) 0.052 (0.027) 0.075 (0.066) 0.026 (0.026) NumLongPsil_NumTotWords 0.033 (0.024) 0.080 (0.042) 0.130 (0.118) 0.041 (0.039) NumMediumPsil_NumTotSlb 0.077 (0.023) 0.112 (0.042) 0.111 (0.049) 0.070 (0.025) NumMediumPsil_NumTotWords 0.133 (0.038) 0.173 (0.066) 0.187 (0.085) 0.112 (0.043) NumShortPsil_NumTotSlb 0.029 (0.020) 0.029 (0.021) 0.025 (0.014) 0.012 (0.008) NumShortPsil_NumTotWords 0.050 (0.033) 0.044 (0.031) 0.041 (0.023) 0.020 (0.014) On the other hand, the highest frequency of short silent pauses was found in controls (one every 34.5 syllables or 20 words), followed by the lvPPA (a short pause every 34.5 syl- lables and 22.7 words) and nfvPPA groups (one every 40 syllables or 24.4 words). The lowest values corresponded to the svPPA group (a short silent pause every 83.3 syllables or 50 words). As for medium silent pauses, they were much more frequent in the nfvPPA (one every 9.0 syllables or 5.3 words) and lvPPA groups (1/9.0 syllables or 1/5.8 words) than in controls (1/13.0 syllables or 1/7.5 words) or the svPPA group (1/14.3 syllables or 1/8.9 words). 3.4.1. Atypicality of Each PPA Group We compared each PPA group with controls using linear regression models, separately for each parameter. The estimates are reported in Appendix A, Table A14. The results show that lvPPA differed from controls in the number of silent pauses per syllable (p = 0.006) and word (p = 0.004), as well as in the frequency of overall pauses (per syllable: p = 0.015; per word: p = 0.048). In all cases, the lvPPA group produced pauses more frequently than controls (silent pauses: 0.193 vs. 0.126/syllable and 0.298 vs. 0.216/word; overall pauses: 0.293 vs. 0.201/syllable and 0.451 vs. 0.345/word). No other significant effects were found. The same parameters significantly distinguished the nfvPPA group and controls: the number of silent pauses and overall pauses per syllable (silent: p = 0.002; overall: p = 0.009) and words (silent: p = 0.004; overall: p = 0.016). As with the lvPPA group, the frequency of silent pauses and overall pauses per syllable and word were much more frequent in the nfvPPA group than in controls (silent pauses: 0.210 vs. 0.126/syllable and 0.357 vs. 0.216/word; overall pauses: 0.301 vs. 0.201/syllable and 0.511 vs. 0.345/word). Again, no other significant effects were found. Regarding the svPPA group, the only significant effects were observed in the number of filled pauses per syllable (p = 0.036) and word (p = 0.022) and in the overall pause frequency per word (p = 0.018). In all cases, the svPPA group produced fewer pauses than controls (0.011 vs. 0.022 filled pauses/syllable, 0.018 vs. 0.037 filled pauses/word, 0.253 vs. 0.345 overall pauses/word). The estimates yielded by further comparisons of each PPA group with controls in terms of the number of long, medium, and short silent pauses are reported in Appendix A, Table A15. We reported above a higher frequency of overall silent pauses in the lvPPA group than in controls, but these supplementary analyses showed that such differences appeared only for long silent pauses (0.052 vs. 0.020/syllable, p = 0.002; and 0.080 vs. 0.033/word, p = 0.003) and for medium silent pauses per syllable (0.112 vs. 0.077 pauses/syllable, p = 0.025). In addition, the lvPPA group produced more medium silent pauses per word than did controls (0.173 vs. 0.133 pauses/word), but this contrast did not reach significance (p = 0.086). No significant effects were shown in short pause frequency, either per syllable or per word. Languages 2023, 8, 45 16 of 44 Similarly, the nfvPPA group only differed from controls in the number of long silent pauses per syllable (0.075 vs. 0.020 pauses/syllable, p = 0.014) and per word (0.130 vs. 0.033 pauses/word, p = 0.016). As for the svPPA group, which did not differ from controls in overall silent pause frequency, these results show that no difference was significant in the frequency of long or medium pauses, but that the svPPA group produced significantly fewer short silent pauses than controls, both per syllable (0.012 vs. 0.029 pauses/syllable, p = 0.025) and per word (0.020 and 0.050 pauses/word, p = 0.020). 3.4.2. (Dis)Similarity among PPA Groups We investigated whether pause frequency per syllable and word could be used to dis- tinguish the three variants of PPA by means of linear regression models of each parameter considered as a function of group (lvPPA, nfvPPA, and svPPA). The estimates are reported in Appendix A, Table A16. Significant effects of group were found on only two pause parameters: the frequency of silent pauses (per syllable: p = 0.002; per word: p = 0.001) and the frequency of overall pauses (per syllable: p = 0.003; per word: p = 0.002). The post hoc analyses showed that the svPPA group produced significantly fewer silent pauses than the other two groups per syllable (0.108 vs. lvPPA = 0.193 and nfvPPA = 0.210 pauses/syllable) and word (0.172 vs. lvPPA = 0.298 and nfvPPA = 0.357 pauses/word). Similar contrasts were observed in the number of overall pauses per syllable (0.159 vs. lvPPA = 0.293 and nfvPPA = 0.301 pauses/syllable) and word (0.253 vs. lvPPA = 0.451 and nfvPPA = 0.511 pauses/syllable). No significant differences between the lvPPA and nfvPPA groups were found for any of the parameters under consideration. The results of supplementary analyses carried out on the effects of group on the frequency of long, medium, and short silent pauses are reported in Appendix A, Table A17. The results show a significant effect of group on the number of long silent pauses per word (p = 0.045). The post hoc analyses revealed a single significant contrast between the nfvPPA and svPPA groups (p = 0.0364): the nfvPPA group produced twice as many long silent pauses per word (0.511) than the svPPA group (0.253). No other significant contrasts were found. In addition, the effect of group on the other parameters considered did not reach significance. 3.5. Pause–Speech and Pause–Total Duration Ratios The proportion of pause time in relation to the duration of speech or the total duration of both speech and pauses has also been suggested to be atypical in some variants of PPA. In our study (see Table 10), the lowest overall pause–speech and pause–total duration ratio corresponded, as expected, to controls (58.15% and 39.95%, respectively) and followed by the svPPA group (63.18% and 39.80%, respectively). The highest values were observed in the lvPPA (98.64% and 53.26%) and nfvPPA groups (157.40% and 55.66%). Table 10. Mean and standard deviation values of pause–speech and pause–total duration ratios, by type and group. Control lvPPA nfvPPA Parameter svPPA (N = 9) (N = 11) (N = 13) (N = 10) R_DurPsil_DurSpeech 37.268 (16.706) 72.598 (24.272) 133.141 (149.431) 49.590 (31.506) R_DurPsil_DurTot 25.095 (8.238) 38.868 (8.565) 43.969 (20.406) 30.353 (12.832) R_DurPfill_DurSpeech 6.436 (3.330) 9.854 (10.483) 8.739 (13.139) 2.742 (2.377) R_DurPfill_DurTot 4.509 (2.144) 5.202 (4.974) 3.328 (2.664) 2.006 (1.851) R_DurSlbLONG_DurSpeech 14.441 (5.919) 16.183 (7.316) 15.519 (8.204) 10.851 (6.527) R_DurSlbLONG_DurTot 10.345 (4.568) 9.195 (4.697) 8.364 (5.733) 7.436 (4.827) R_DurPausesALL_DurSpeech 58.145 (14.790) 98.635 (25.851) 157.398 (155.686) 63.183 (29.295) R_DurPausesALL_DurTot 39.949 (6.205) 53.262 (7.239) 55.661 (17.683) 39.797 (11.042) Languages 2023, 8, 45 17 of 44 The proportion of time devoted to silent pauses over speech duration and total du- ration followed the same pattern: it was lower in controls (32.27% of speech duration and 25.10% of total duration), followed by the svPPA group (49.59% and 30.35%), and much higher in the lvPPA (72.60% and 38.87%) and nfvPPA groups (133.14% and 43.97%, respectively). On average, the filled pause–speech ratio varied from 2.74% in the svPPA group to 9.85% in the lvPPA group; controls and the nfvPPA group presented intermediate values (6.44% and 8.74%, respectively). Similarly, the lengthened syllables–speech ratio varied from 10.85% in the svPPA group to 16.18% in the lvPPA group, with intermediate values observed in controls (14.44%) and the nfvPPA group (15.52%). As for the percentage of total duration devoted to filled pauses and lengthened syllables, the lowest mean values corresponded to the svPPA (2.01% and 7.44%, respectively) and nfvPPA groups (3.33% and 8.36%, respectively), and the highest ones were observed in controls (4.51% and 10.35%) and the lvPPA group (5.20% and 9.20%, respectively). 3.5.1. Atypicality of Each PPA Group Each group of participants with PPA was compared with controls by means of linear regression models of the effect of group on different parameters related to pause–speech and pause–total duration ratios (see Appendix A, Table A18). The results show that the lvPPA group differed significantly from controls in the percentage of silent pause time over speech (p = 0.001) and total duration (p = 0.001), as well as in the proportion of overall pause time, in relation to both speech (p = 0.000) and total duration (p = 0.000). Compared to controls, lvPPA was associated with a higher silent pause–speech ratio (72.60% vs. 37.27%) and silent pause–total duration ratio (38.87% vs. 25.10%, respectively). Similarly, the proportion of time devoted to overall pauses was much greater in the lvPPA group than in controls (98.64% vs. 58.15% of speech time, and 53.26% vs. 39.95% of total duration, respectively). No significant effects were found in pause–speech or pause–total duration ratio for either filled pauses or lengthened syllables. A significant effect was found for the nfvPPA group on the same parameters: silent pause–speech ratio (p = 0.048), silent pause–total duration ratio (p = 0.01), overall pause– speech ratio (p = 0.048), and overall pause–total duration ratio (p = 0.000). In this group, silent pause duration equalled on average 133.14% of speech duration (vs. 37.27% in controls) and 43.97% of total duration (vs. 25.10% in controls). The percentage of time devoted to pauses overall was also much higher in the nfvPPA group than in controls, in relation to both speech (157.40% vs. 58.15%) and total duration (55.66% vs. 39.95%, respectively). Again, no significant effects were found for filled pauses or lengthened syllables. With regard to the svPPA group, the results show significant effects only on the percentage of time of filled pauses over both speech time (p = 0.012) and total duration (p = 0.013). Compared to controls, svPPA participants allowed a proportionally smaller amount of time for filled pauses than did controls (pause–speech ratio: 2.74% vs. 6.44%; pause–total duration ratio: 2.01% vs. 4.51%). 3.5.2. (Dis)Similarity among PPA Groups We report in Appendix A, Table A19, the results of the linear regression models carried out in order to investigate whether any of the parameters related to pause–speech or pause–total duration ratio could be used to differentiate the three PPA groups from each other. No significant group effect was found on any of the parameters considered, with only one exception: the proportion of total duration devoted to pauses overall (p = 0.019). The post hoc analyses showed that the svPPA group differed from the other two PPA groups by showing lower values for the pause–total duration ratio (38.80% vs. lvPPA = 53.26%, p = 0.0452; and vs. nfvPPA = 55.66%, p = 0.0239). Languages 2023, 8, 45 18 of 44 4. Discussion The goal of this study was to determine whether measures related to pausing could be used to distinguish the three main variants of primary progressive aphasia from healthy controls and also to differentiate the three variants of PPA from each other. We will examine the light that our findings shed on these two questions and then address certain methodological issues that bear on our results. 4.1. Atypicalities in PPA For several of the parameters examined, our results reveal no significant differences between controls and each of the variants of PPA. However, other parameters did differ significantly across groups. Most notably, the frequency of total pauses per word was much higher in the lvPPA and nfvPPA groups (every 2.22 and 1.9 words, respectively) than in the control group (every 2.9 words) and significantly lower in the svPPA group (every 3.95 words). This frequency seems to be the most reliable index of different pausing patterns in PPA types (Ash et al. 2013; Fraser et al. 2014; Potagas et al. 2022; Wilson et al. 2010) and apparently can also help to distinguish variants of vascular aphasia (Angelopoulou et al. 2018). This reliability may be due to the fact that this parameter does not depend on speech and articulatory rates, which are highly variable as a result of both individual personality traits (Goldman-Eisler 1968) and the particularities of speech and language impairments (Christenfeld and Creager 1996). Additionally, in the present study, each group with PPA presented atypical values in a different set of pause-related metrics, which we will now examine in detail. 4.1.1. lvPPA Participants with lvPPA presented higher values than controls in a set of dimensions, mostly related to the frequency of silent pauses per second of speech, per syllable, and per word. This difference seems to be related to an increased number of long silent pauses (>1 s) and to a significantly greater duration of silent pauses and overall pauses relative to speech and total speech duration. The median duration of silent pauses was also longer in participants with lvPPA, albeit not significantly. These results are congruent with previous studies (Ash et al. 2013; Ballard et al. 2014; Boschi et al. 2017; Cordella et al. 2017; Nevler et al. 2019; Poole et al. 2017; Potagas et al. 2022; Yunusova et al. 2016), and they may explain why lvPPA, where diagnostic features do not include dysfluency (Gorno-Tempini et al. 2011), has been categorised as fluent by some researchers but nonfluent by others (Gorno-Tempini et al. 2008; Hilger et al. 2014; Wilson et al. 2010). 4.1.2. nfvPPA Like the lvPPA group, participants with nfvPPA differed from controls in their higher frequency and proportion of time of silent (and overall) pauses, especially long silent pauses. However, the difference in the number of overall pauses per second of speech was not significant. In addition, compared to controls, nfvPPA participants produced longer silent pauses (1.377 s vs. 0.604 s) and longer (0.656 s vs. 0.585 s) and more variable (SD = 0.285 s vs. 0.179 s) lengthened syllables. By contrast, the standard deviation of the duration of filled pauses was lower than in controls (SD = 0.320 s vs. 0.429 s). Our results are similar to those of previous studies (Ballard et al. 2014; Cordella et al. 2017; Nevler et al. 2019; Poole et al. 2017; Potagas et al. 2022; Rohrer et al. 2010; Wilson et al. 2010; Yunusova et al. 2016), despite some inconsistencies (which could be due to methodological discrepancies, see below), to wit: • The mean duration of silent pauses is systematically reported as longer in nfvPPA than in controls, but not always significantly so (Nevler et al. 2019; Yunusova et al. 2016); • Significantly higher median and standard values of the duration of silent pauses (Ballard et al. 2014) and a higher frequency of filled pauses per word (Wilson et al. 2010) in nfvPPA than in controls have been reported, while such differences have been found to be non-significant in other studies (including this one). Languages 2023, 8, 45 19 of 44 4.1.3. svPPA Several parameters distinguished svPPA participants from controls, primarily lower frequencies of filled pauses (per syllable and word) and short silent pauses (per second of speech, syllable, and word), as well as a low filled pauses–speech ratio. Additionally, lengthened syllables were shorter (0.520 s vs. 0.585 s) and less variable (SD: 0.156 s vs. 0.179 s) in svPPA participants compared to healthy controls. As individuals with svPPA are generally regarded as being fluent, research on the tem- poral characteristics of their speech is far less common and frequently focuses only on silent pauses. Similar to our results, most studies have found no significant differences between people with svPPA and healthy speakers in the mean duration of silent pauses (Cordella et al. 2017; Nevler et al. 2019) or in the proportion of time that they occupy (Cordella et al. 2017). However, Nevler et al. (2019) found a significantly increased frequency of silent pauses per minute of speech in svPPA participants compared to controls. Research on filled pauses in svPPA (Fraser et al. 2014; Wilson et al. 2010) has not looked at their duration or the proportion of speech they occupy but has reported their frequency per word to be similar in participants with svPPA and healthy speakers. Our results have led to a different conclusion in that we found no difference between the two groups in duration in terms of mean, median, or standard deviation, but the frequency of filled pauses per word was significantly lower in svPPA participants than in controls (this study, 0.018 vs. 0.037 pauses per second; Fraser et al. (2014), 0.053 vs. 0.054; Wilson et al. (2010), 0.04 for both groups). Moreover, similar differences were observed in the speech time (or total duration) devoted to filled pauses, with svPPA participants demonstrating less than half that of controls. Our findings may be interpreted as a consequence of individuals with svPPA not self-monitoring their speech, resulting in a lower number of pauses (Oomen et al. 2001, 2005; Postma 2000). Similar effects have been reported in Wernicke’s aphasia (Christenfeld and Creager 1996). 4.1.4. Dysfluency in the Three Variants of PPA Overall, groups with PPA showed atypical values in several temporal variables; they can therefore be considered dysfluent in the sense that they present some ‘abnormality of fluency’ (Wingate 1984). For lvPPA and nfvPPA participants, dysfluency was characterised by significantly more frequent pauses overall (particularly long silent ones), both per unit of time and per syllable or word, as well as by a higher proportion of (speech and total) time devoted to these pauses. The mean (nfvPPA) and median (lvPPA) duration of silent pauses were also significantly higher. Such observations suggest that these two PPA variants may be regarded as hypo-fluent; that is, they show reduced fluency, albeit to varying degrees. This dysfluency may arise from impaired phono-lexical access and difficulties in syntactic processing. Additionally, unlike lvPPA, nfvPPA was associated with longer lengthened syllables, probably due to a specific impairment in articulatory planning (apraxia of speech), resulting in a decreased articulation rate. svPPA participants presented a lower (atypical) frequency of overall pauses per word, especially in both filled pauses and short silent pauses per syllable and word, and the proportion of (speech and total) time devoted to filled pauses. Shorter lengthened syllables, commonly related to a faster articulation rate, were also observed. Their fluency was therefore greater than that of controls, which suggests that hyper-fluency can be regarded as a feature of svPPA (Kirsner et al. 2005). These results highlight the fact that (dys)fluency is a multifaceted concept (Götz 2013) that involves both production and perception and depends on both articulatory and prosodic abilities, and can impact various things, such as accuracy, lexical diversity, and sentence structure. Even though the three variants of PPA can be regarded as dysfluent, as manifested by the differences observed between each of them and the control group in several pause-related values, at least two dimensions should be distinguished. Firstly, motoric-related phenomena include the duration of lengthened syllables, which depends on the articulatory rate and, consequently, on motoric deficits, allowing us to Languages 2023, 8, 45 20 of 44 classify svPPA as hyper-fluent, nfvPPA as hypo-fluent, and lvPPA as not atypical. Secondly, pausing phenomena attributable to higher-level speech processing include the overuse in lvPPA and nfvPPA of pauses (in particular, long silent ones), which have often been attributed to specific difficulties in phono-lexical retrieval and grammatical encoding. However, in our study, atypical pausing behaviour was also observed in svPPA participants, who produced much fewer pauses per word than controls (especially filled and short silent pauses). Since this PPA variant is characterised by naming difficulties related to their semantic deficit and paragrammatisms, such dysfluent characteristics cannot be attributed to preserved speech production. An overall interpretation of these two opposite behaviours is that they may form part of more general processes, such as the degree of attention speakers pay to their speech (Christenfeld and Creager 1996). We hypothesised above that the hyper-fluency in individuals with svPPA may be due to the reduced attention they pay to their speech, because of either strategic decisions (Postma 2000; Sahraoui et al. 2015) or higher levels of anosognosia (Tondelli et al. 2021), leading to decreased self-monitoring. It has already been reported that people with svPPA tend not to grasp for ‘lost’ words in a conversation (Marshall et al. 2018), contrary to what is observed in the other two variants of PPA. Therefore, hypo-fluency in lvPPA and nfvPPA, and hyper-fluency in svPPA, could result from over-monitoring and under-monitoring the speech output, respectively. 4.2. (Dis)Similarity among the Three Variants of PPA Like in previous studies, none of the parameters analysed here by itself sufficed to differentiate the three variants of PPA. The group effect was significant only for a few parameters, mostly related to silent pauses and overall pause frequency. Post hoc analyses showed that most of these metrics differentiated svPPA from both lvPPA and nfvPPA: svPPA presented lower values of (a) the frequency of silent pauses and overall pauses per second of speech, per syllable and word, (b) the overall pause–total duration ratio, and (c) variability in lengthened syllable duration. The contrasts between svPPA and lvPPA and nfvPPA were significant for almost all the metrics mentioned above, except for the number of overall pauses per second of speech, in which only the contrast with lvPPA was significant, along with the number of long silent pauses per word and the standard deviation of lengthened pause duration, in which svPPA differed significantly only from nfvPPA. Consistent with our results, no significant contrasts between lvPPA and nfvPPA in any of the temporal measures related to pausing have been reported when considered separately, except in a few studies. In Ballard et al. (2014), nfvPPA was associated with higher median and standard deviation values of the duration of silent pauses. Our data also showed such differences, albeit not significant, which may be explained by the task type (reading vs. picture description). Another exception is the number of silent pauses per word, which was higher in nfvPPA than in lvPPA patients in the study by Potagas et al. (2022). In our study, on the other hand, this contrast did not reach significance, possibly due to differences in the number of participants between the two studies. Furthermore, consistent with our results, several parameters, among them the number of silent pauses per second of speech time (Nevler et al. 2019) and per word (Potagas et al. 2022), have been previously reported as making it possible to distinguish svPPA from the other two main variants of PPA. It is worth noting, however, that in Potagas et al. (2022), the svPPA groups significantly differed from the other two PPA groups in the frequency of silent pauses in the personal story task but only from nfvPPA in the picture description task. Additionally, Cordella et al. (2017) found a longer mean silent pause duration in nfvPPA than in svPPA patients, while no significant differences were found either in our study or in others, such as Nevler et al. (2019). Taken together, these results show that indices related to the frequency of pauses (overall and silent ones, but not filled pauses or lengthened syllables, per unit of time and per syllable or word) are more suitable than duration values for differentiating the variants Languages 2023, 8, 45 21 of 44 of PPA, mostly svPPA from the other two. However, despite characteristic differences in pausing behaviour among the three groups, no single pause-related parameter differen- tiated them. Further multi-parametric analyses should be conducted to determine what combination of parameters might permit the differentiation of each main variant of PPA from the other two. 4.3. Methodological Considerations As previously mentioned, some differences between our results and previous studies may be due to methodological decisions related to task types, speech sample processing, or the parameters and languages analysed. Task-dependent differences may account for some discrepancies. For instance, picture description is more demanding in terms of lexical retrieval than reading tasks and therefore results in more word-finding pauses. This may explain why, unlike the findings of our study, no mean duration differences were found between nfvPPA participants and healthy controls in Yunusova et al. (2016). Moreover, picture description requires more attention to grammatical encoding or text planning, which increases the number and variability of long pauses, not only in persons with PPA but also in healthy speakers, diminishing the contrast among different groups. Hence, it is not surprising that the reported increase in the median values of silent pause duration in nfvPPA patients (Yunusova et al. 2016) and the standard deviation of the duration of silent pauses in lvPPA patients (Ballard et al. 2014; Poole et al. 2017) was not significant in our study. Other discrepancies may be due to speech sampling and quantitative measurements. In our study, the labelling of both pause events and syllables was corrected manually, allowing us to include all kinds of pauses (silent, filled, or lengthened syllables), regardless of their length. This time-consuming procedure was replaced in other studies by fully automatic silence detection algorithms (Nevler et al. 2019), which are highly prone to align- ment errors (Brognaux and Drugman 2016). In addition, speech samples were sometimes pre-processed and filled pauses and non-speech vocalisations were zeroed in the waveform (Cordella et al. 2017), which may affect the reporting of pause frequency and duration. Thus, even if most of the research above supports our results, methodological issues may explain differences such as the lower frequency of silent pauses per second found in nfvPPA (Cordella et al. 2017) and svPPA patients (Nevler et al. 2019). Filled pauses have received less scholarly attention and led to partly inconsistent results. Our study confirmed prior results finding that no significant differences between controls and lvPPA or nfvPPA participants were found in frequency or proportion of speech time for filled pauses and lengthened syllables, nor in mean pause duration. Other studies have found no difference in the number of filled pauses per syllable or word between lvPPA patients and healthy speakers (Poole et al. 2017; Wilson et al. 2010). Most studies also found that nfvPPA patients produced more such pauses than controls, but their values often fell into the normal range (this study, Fraser et al. 2014), the exception being Wilson et al. (2010). Concerning svPPA, only a few studies have reported data on filled pauses (Fraser et al. 2014; Wilson et al. 2010). They mainly conclude that svPPA participants did not differ from controls in the frequency of filled pauses per word, but that they produced fewer filled pauses than lvPPA (only in Wilson et al. 2010) and nfvPPA. By contrast, our results show that svPPA produced significantly fewer filled pauses per word than both controls and nfvPPA patients and the proportion of time of speech devoted to filled pauses was also lower. Such inconsistencies may be due to the elicitation task used (Fraser et al. 2014), since, relative to describing a picture, telling the Cinderella story requires more memory resources, which can induce more filled pauses in svPPA patients, and to potential differences across languages and cultures (Wilson et al. 2010), as pointed out by several authors (Crible et al. 2017; Endrass et al. 2008; Rose and Watanabe 2019). The variables under analysis also distinguish our study from previous work. Although most researchers have focused on silent pauses, to the best of our knowledge, the grouping of silent pauses into three categories as a function of their length has not yet been analysed in Languages 2023, 8, 45 22 of 44 PPA, even if their bi- or tri-modal distribution has repeatedly been reported, in both typical and disordered speech (Angelopoulou et al. 2018; Baditzné Pálvölgyi 2020; Campione and Véronis 2002; Goldman-Eisler 1968; Hird and Kirsner 2010; Kirsner et al. 2005; Parjane et al. 2021; Thomas 2021; Trouvain and Werner 2022). In normal speech, short pauses are often associated with breathing or articulatory phenomena, while medium pauses are linked to demarcative functions that are assumed to aid listeners to parse utterances correctly. In contrast, longer pauses appear only in spontaneous speech and seem to be related to higher cognitive functions, such as word seeking or sentence planning. Pre- and post-articulatory monitoring processes might also lead to a specific distribution of pause duration (Pillai 2006). For example, people with post-stroke aphasia differ from healthy speakers solely in indices related to long pauses, reflecting impaired lexical access or deficits in sentence planning, while short pauses are irrelevant (e.g., Angelopoulou et al. 2018; Hird and Kirsner 2010; Kirsner et al. 2005; Oomen et al. 2001, 2005). Therefore, in our study we decided to include a more fine-grained analysis, and distinguished between short, medium, and long pauses, following the thresholds established in Campione and Véronis (2002). Our study revealed that pausing atypicality did not affect short, medium, and long silent pauses in the same way. In nfvPPA and lvPPA, only long (and medium, in lvPPA) silent pauses presented a higher frequency and proportion of time than controls. The opposite pattern was observed in svPPA, in which atypical values were found only for short pauses, which were less frequent and corresponded to a lower proportion of the time. It may be assumed, therefore, that thresholds based on the distribution of pauses for a specific participant and task can lead to a fuller understanding of individual pausing behaviour. To our knowledge, no previous research has focused on the frequency, duration, or proportion of time of lengthened syllables, considered a hesitation phenomenon, in the spontaneous speech of persons with PPA. It should be emphasised that ‘syllable lengthen- ing’ refers to different concepts, as syllables that are longer than normal can be due to an overall decrease in articulatory rate, prosodic effects (e.g., utterance-final lengthening), or hesitation phenomena (see above, Sections 1 and 2). In our study, this type of hesitation was included and led to some interesting results since specific—and opposite—atypicalities were found in nfvPPA and svPPA, in both duration and variability. They also allowed us to compute holistic parameters that include the three types of hesitation phenomena, namely silent pauses, filled pauses, and lengthened syllables, thereby enabling us to obtain an overall picture of pausing behaviour. 5. Conclusions PPA is a multifaceted condition, and differentiating its variants may be difficult. In addition to biological and neuropathological measurements, the degree of language impairment must be determined for accurate diagnosis. It has been shown that hesitancy phenomena are important indicators of speech processing dysfunction. In this research, a wide number of factors related to silent and filled pauses and syllable lengthening were studied and compared among patients with variants of PPA (lvPPA, nfvPPA, and svPPA) and healthy controls via a picture description task. According to the results, the frequency of pauses per word, especially lengthy pauses, seems to be the measure that best distinguishes between healthy speakers and each of the three major variants of PPA. However, less researched hesitation phenomena, such as filled pauses and lengthened syllables, can also contribute to a better understanding of varied types of dysfluency present in each phenotype. Therefore, we argue that analysing pausing behaviour in detail, as we have done here, might aid in diagnosis and speech treatment. Another point to mention is that, since no single measure distinguishes among the three variants of PPA, new multi-parametric techniques that can capture the complexity of hesitation phenomena are required. For a fuller picture of dysfluency in each variant of PPA, further in-depth study is necessary on the relationship between pausing behaviour and other speech features, such as articulatory mechanisms and speech rate, the length of speech chunks, and the proportion of semantic information provided. Languages 2023, 8, 45 23 of 44 Author Contributions: The two authors participated to a similar extent in each part of the research and in writing, reviewing, and editing this paper. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Instituto de Salud Carlos III (Spanish Ministry of Science). Project identifier: PI19/00882. Title: [Primary progressive aphasia: multimodal characterization of symptoms, physiopathology, and progression.] Afasia primaria progresiva: Caracterización multimodal de los síntomas, fisiopatología, y progresión. PI: Miguel Angel Santos Santos MD, PhD. Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Hospital of Hospital de la Santa Creu i Sant Pau (protocol code IIBSP-REH-2020-88, 13 October 2020). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: Not applicable. Acknowledgments: We are immensely grateful to Miguel Angel Santos-Santos, a neurologist at the Sant Pau Hospital Memory Unit, for sharing speech samples of subjects used in this research. Conflicts of Interest: The authors declare no conflict of interest. Appendix A Table A1. Description of acoustic parameters (in alphabetical order). Parameters Definition Mdn_DurPfill Median of duration of filled pauses Mdn_DurPsil Median of duration of empty pauses Mdn_SlbLONG Median of duration of lengthened syllables Mn_DurPfill Mean duration of filled pauses Mn_DurPsil Mean duration of empty pauses Mn_DurSlbLONG Mean duration of lengthened syllables NumLongPsil_DurSpeech Total number of long empty pauses relative to speech duration NumLongPsil_DurTot Total number of long empty pauses relative to total sample (speech + pauses) duration NumLongPsil_NumTotSlb Total number of long empty pauses relative to total number of syllables NumLongPsil_NumTotWords Total number of long empty pauses relative to total number of words NumMediumPsil_DurSpeech Total number of medium empty pauses relative to speech duration NumMediumPsil_DurTot Total number of medium empty pauses relative to total sample (speech + pauses duration) NumMediumPsil_NumTotSlb Total number of medium empty pauses relative to total number of syllables NumMediumPsil_NumTotWords Total number of medium empty pauses relative to total number of words NumPausesALL_DurSpeech Total number of pauses relative to speech NumPausesALL_DurTot Total number of pauses relative to total sample (speech + pauses duration) NumPausesALL_NumTotSlb Total number of pauses relative to total number of syllables NumPausesALL_NumTotWords Total number of pauses relative to total number of words NumPfill_DurSpeech Total number of filled pauses relative to speech duration NumPfill_DurTot Total number of filled pauses relative to total sample (speech + pauses duration) NumPfill_NumTotSlb Total number of filled pauses relative to total number of syllables NumPfill_NumTotWords Total number of filled pauses relative to total number of words NumPsil_DurSpeech Total number of empty pauses relative to speech duration NumPsil_DurTot Total number of empty pauses relative to total sample (speech + pauses duration) NumPsil_NumTotSlb Total number of empty pauses relative to total number of syllables NumPsil_NumTotWords Total number of empty pauses relative to total number of words NumShortPsil_DurSpeech Total number of short empty pauses relative to speech duration NumShortPsil_DurTot Total number of short empty pauses relative to total sample (speech + pauses duration) NumShortPsil_NumTotSlb Total number of short empty pauses relative to total number of syllables NumShortPsil_NumTotWords Total number of short empty pauses relative to total number of words NumSlbLONG_DurSpeech Total number of lengthened syllables relative to speech duration NumSlbLONG_DurTot Total number of lengthened syllables relative to total sample (speech + pauses duration) NumSlbLONG_NumTotSlb Total number of lengthened syllables relative to total number of syllables Languages 2023, 8, 45 24 of 44 Table A1. Cont. Parameters Definition NumSlbLONG_NumTotWords Total number of lengthened syllables relative to total number of words R_DurPausesALL_DurSpeech Ratio of duration of pausing relative to speech R_DurPausesALL_DurTot Ratio of duration of pausing to total duration of speech (speech + pauses) R_DurPfill_DurSpeech Ratio of duration of filled pauses relative to speech R_DurPfill_DurTot Ratio of duration of filled pauses relative to total duration of speech (speech + pauses) R_DurPsil_DurSpeech Ratio of duration of empty pauses relative to speech R_DurPsil_DurTot Ratio of duration of empty pauses relative to total duration of speech (speech + pauses) R_DurSlbLONG_DurSpeech Ratio of duration of lengthened syllables relative to speech R_DurSlbLONG_DurTot Ratio of duration of lengthened syllables relative to total duration of speech (speech + pauses) R_NumLongPsil_NumTotPsil Ratio of the number of long empty pauses relative to total number of empty pauses R_NumMediumPsil_NumTotPsil Ratio of the number of medium empty pauses relative to total number of empty pauses R_NumShortPsil_NumTotPsil Ratio of the number of short empty pauses relative to total number of empty pauses SD_DurPfill Standard deviation of duration of filled pauses SD_DurPsil Standard deviation of duration of empty pauses SD_DurSlbLONG Standard deviation of duration of lengthened syllables Table A2. Mixed-effects linear regression models of pause duration, by group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values. Parameter Contrast B SE(B) df t p Intercept (=control) 0.62809 0.08233 21.37626 7.629 1.56 × 10−7 *** control–lvPPA lvPPA 0.23301 0.11223 21.5892 2.076 0.05 F(1, 21.589) = 4.310, p = 0.050 Intercept (=control) 0.6305 0.2339 17.4693 2.696 0.0151 * control–nfvPPA nfvPPA 0.7314 0.3445 18.6156 2.123 0.0474 * Dur_Psil F(1, 18.616) = 4.508, p = 0.047 Intercept (=control) 0.63 0.1029 11.37 6.12 6.53 × 10−5 *** control–svPPA svPPA 0.2015 0.1595 13.1578 1.263 0.228 F(1, 13.158) = 1.596, p = 0.228 Intercept (=control) 0.63038 0.05021 19.59174 12.554 8.03 × 10−11 *** control–lvPPA lvPPA −0.04567 0.07037 19.75771 −0.649 0.524 F(1, 19.758) = 0.421, p = 0.524 Intercept (=control) 0.637425 0.057696 13.336115 11.048 4.35 × 10−8 *** control–nfvPPA nfvPPA 0.001624 0.098047 22.391093 0.017 0.987 Dur_Pfill F(1, 22.391) = 0.000, p = 0.987 Intercept (=control) 0.63295 0.05282 12.41269 11.983 3.46 × 10−8 *** control–svPPA svPPA −0.14479 0.11353 37.97495 −1.275 0.21 F(1, 37.975) = 1.626, p = 0.210 Intercept (=control) 0.57837 0.0327 18.95185 17.689 3.07 × 10−13 *** control–lvPPA lvPPA 0.0134 0.04511 20.13137 0.297 0.77 F(1, 20.131) = 0.088, p = 0.770 Intercept (=control) 0.58405 0.01574 7.35739 37.108 1.22 × 10−9 *** control–nfvPPA nfvPPA 0.07254 0.02955 17.64642 2.455 0.0247 * Dur_SlbLONG F(1, 17.646) = 6.026, p = 0.025 Intercept (=control) 0.58325 0.01482 9.03557 39.343 2.04 × 10−11 *** control–svPPA svPPA −0.06468 0.02792 17.46701 −2.317 0.0329 * F(1, 17.467) = 5.368, p = 0.033 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Languages 2023, 8, 45 25 of 44 Table A3. Mixed-effects linear regression models of the standard deviation of pause duration, by group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values. Parameter Contrast B SE(B) t p Intercept (=control) 0.5936 0.1249 4.752 9.63 × 10−5 *** control–lvPPA lvPPA 0.1733 0.1697 1.021 0.318 F(1) = 1.042, p = 0.318 Intercept (=control) 0.5936 0.3722 1.595 1.27 × 10−1 control–nfvPPA nfvPPA 0.9894 0.5394 1.834 0.0823 SD_DurPsil F(1) = 3.364, p = 0.082 Intercept (=control) 0.5936 0.1586 3.744 1.49 × 10−3 ** control–svPPA svPPA 0.1819 0.2364 0.77 0.45149 F(1) = 0.592, p = 0.451 Intercept (=control) 0.413 0.05915 6.982 8.92 × 10−7 *** control–lvPPA lvPPA −0.13717 0.08009 −1.713 0.102 F(1) = 2.933, p = 0.102 Intercept (=control) 0.413 0.06607 6.251 6.76 × 10−6 *** control–nfvPPA nfvPPA −0.219 0.09343 −2.344 0.0308 * SD_DurPfill F(1) = 5.494, p = 0.031 Intercept (=control) 0.413 0.07802 5.294 1.13 × 10−4 *** control–svPPA svPPA −0.18967 0.1274 −1.489 0.158738 F(1) = 2.216, p = 0.159 Intercept (=control) 0.16909 0.02024 8.355 2.85 × 10−8 *** control–lvPPA lvPPA 0.02322 0.0275 0.844 0.408 F(1) = 0.713, p = 0.408 Intercept (=control) 0.16909 0.02897 5.836 1.27 × 10−5 *** control–nfvPPA nfvPPA 0.09891 0.04199 2.356 0.0294 * SD_DurSlbLONG F(1) = 5.549, p = 0.029 Intercept (=control) 0.16909 0.01594 10.61 3.56 × 10−9 *** control–svPPA svPPA −0.05576 0.02376 −2.347 0.0306 * F(1) = 5.508, p = 0.031 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A4. Mixed-effects linear regression models of median pause duration, by group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values. Parameter Contrast B SE(B) t p Intercept (=control) 0.50318 0.05498 9.152 5.90 × 10−9 *** control–lvPPA lvPPA 0.1752 0.0747 2.345 0.0284 * F(1) = 5.501, p = 0.028 Intercept (=control) 0.5032 0.1047 4.806 1.23 × 10−4 control–nfvPPA nfvPPA 0.2909 0.1517 1.917 0.070353 Mdn_DurPsil F(1) = 3.676, p = 0.070 Intercept (=control) 0.50318 0.09477 5.309 4.78 × 10−5 *** control–svPPA svPPA 0.15982 0.14128 1.131 0.273 F(1) = 1.280, p = 0.273 Languages 2023, 8, 45 26 of 44 Table A4. Cont. Parameter Contrast B SE(B) t p Intercept (=control) 0.52445 0.06006 8.732 1.34 × 10−8 *** control–lvPPA lvPPA 0.05416 0.08161 0.664 0.514 F(1) = 0.440, p = 0.514 Intercept (=control) 0.52445 0.07198 7.286 6.52 × 10−7 *** control–nfvPPA nfvPPA 0.01065 0.10431 0.102 0.92 Mdn_DurPfill F(1) = 0.010, p = 0.920 Intercept (=control) 0.52445 0.0598 8.77 6.46 × 10−8 *** control–svPPA svPPA −0.09734 0.08914 −1.092 0.289 F(1) = 1.192, p = 0.289 Intercept (=control) 0.53664 0.03176 16.895 4.38 × 10−14 *** control–lvPPA lvPPA 0.0219 0.04316 0.508 0.617 F(1) = 0.258, p = 0.617 Intercept (=control) 0.53664 0.0293 18.316 1.57 × 10−13 *** control–nfvPPA nfvPPA 0.07936 0.04246 1.869 0.0771 Mdn_DurSlbLONG F(1) = 3.494, p = 0.077 Intercept (=control) 0.53664 0.02344 22.89 3.26 × 10−14 *** control–svPPA svPPA −0.03489 0.03613 −0.966 0.348 F(1) = 0.932, p = 0.348 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A5. Linear regression models of pause duration, by group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values of the pairwise contrasts between the three PPA groups. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA −0.499585971 0.296278111 28.17736763 −1.686206144 0.2280 lvPPA–svPPA 0.027988754 0.310520944 29.88620046 0.090134836 0.9955 Dur_Psil nfvPPA–svPPA 0.527574725 0.332519936 31.18010197 1.586595774 0.2663 F(2, 28.582) = 1.771, p = 0.188 lvPPA–nfvPPA −0.064391969 0.079882149 21.28827929 −0.806087088 0.703 lvPPA–svPPA 0.098126945 0.099215587 40.08238697 0.98902751 0.588 Dur_Pfill nfvPPA–svPPA 0.162518914 0.110399422 49.95845659 1.472099323 0.313 F(2, 42.376) = 1.112, p = 0.338 lvPPA–nfvPPA −0.069768127 0.054240504 27.22960508 −1.286273581 0.415 lvPPA–svPPA 0.070984397 0.057110031 26.42537252 1.242940962 0.439 Dur_SlbLONG nfvPPA–svPPA 0.140752524 0.063565198 30.49386627 2.21430169 0.085 . F(2, 31.008) = 2.478, p = 0.100 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A6. Linear regression models of standard deviation of pause duration, by group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values of the pairwise contrasts between the three PPA groups. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA −0.816076923 0.45286852 29 −1.802017333 0.1867 lvPPA–svPPA −0.008632479 0.466872508 29 −0.018490013 0.9998 SD_DurPsil nfvPPA–svPPA 0.807444444 0.494692626 29 1.632214433 0.2486 F(2) = 1.958, p = 0.159 Languages 2023, 8, 45 27 of 44 Table A6. Cont. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA 0.081833333 0.067443384 25 1.2133634 0.4565 lvPPA–svPPA 0.0525 0.078756904 25 0.666608221 0.7848 SD_DurPfill nfvPPA–svPPA −0.029333333 0.081339781 25 −0.360627148 0.9310 F(2) = 0.758, p = 0.479 lvPPA–nfvPPA −0.075692308 0.040313716 29 −1.877582018 0.1633 lvPPA–svPPA 0.078974359 0.041560331 29 1.900234125 0.1567 SD_DurSlbLONG nfvPPA–svPPA 0.154666667 0.044036839 29 3.512210954 0.0041 ** F(2) = 6.170, p = 0.006 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A7. Linear regression models of median pause duration, by group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values of the pairwise contrasts between the three PPA groups. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA −0.115715385 0.155176451 29 −0.745701967 0.7386 lvPPA–svPPA 0.015384615 0.15997495 29 0.096168903 0.9949 Mdn_DurPsil nfvPPA–svPPA 0.1311 0.169507578 29 0.77341675 0.7220 F(2) = 0.381, p = 0.687 lvPPA–nfvPPA 0.043515385 0.100720181 29 0.432042359 0.9026 lvPPA–svPPA 0.151504274 0.103834737 29 1.459090459 0.3250 Mdn_DurPfill nfvPPA–svPPA 0.107988889 0.110022068 29 0.981520265 0.5942 F(2) = 1.085, p = 0.351 lvPPA–nfvPPA −0.057461538 0.049163265 28 −1.168790129 0.4812 lvPPA–svPPA 0.056788462 0.052522024 28 1.081231408 0.5333 Mdn_DurSlbLONG nfvPPA–svPPA 0.11425 0.055442108 28 2.060708094 0.1166 F(2) = 2.136, p = 0.137 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A8. Linear regression models of the proportion of the total number of long, medium, and short silent pauses, by group. Estimates (B), standard errors (SE(B)), t-values, and p-values. Parameter Contrast B SE(B) t p Intercept (=control) 0.16055 0.04092 3.924 0.000726 *** control–lvPPA lvPPA 0.12022 0.0556 2.162 0.041723 * F(1) = 4.676, p = 0.042 Intercept (=control) 0.16055 0.05463 2.939 0.00843 ** control–nfvPPA nfvPPA 0.17285 0.07917 2.183 0.04177 * R_NumLongPsil_NumTotPsil F(1) = 4.767, p = 0.042 Intercept (=control) 0.16055 0.05139 3.124 0.00586 ** control–svPPA svPPA 0.06601 0.0766 0.862 0.40018 F(1) = 0.743, p = 0.400 Intercept (=control) 0.61927 0.03964 15.623 2.16 × 10−13 *** control–lvPPA lvPPA −0.03381 0.05386 −0.628 0.537 F(1) = 0.394, p = 0.537 Intercept (=control) 0.61927 0.04368 14.178 1.48 × 10−11 *** control–nfvPPA nfvPPA −0.07857 0.06329 −1.241 0.23 R_NumMediumPsil_NumTotPsil F(1) = 1.541, p = 0.230 Intercept (=control) 0.61927 0.04362 14.198 3.22 × 10−11 *** control–svPPA svPPA 0.03351 0.06502 0.515 0.613 F(1) = 0.266, p = 0.613 Languages 2023, 8, 45 28 of 44 Table A8. Cont. Parameter Contrast B SE(B) t p Intercept (=control) 0.22045 0.03036 7.261 2.84 × 10−7 *** control–lvPPA lvPPA −0.08661 0.04126 −2.099 0.0475 * F(1) = 4.407, p = 0.047 Intercept (=control) 0.22045 0.03038 7.257 6.90 × 10−7 *** control–nfvPPA nfvPPA −0.09445 0.04402 −2.146 0.045 * R_NumShortPsil_NumTotPsil F(1) = 4.604, p = 0.045 Intercept (=control) 0.22045 0.03304 6.672 2.93 × 10−6 *** control–svPPA svPPA −0.09979 0.04926 −2.026 0.0579 F(1) = 4.104, p = 0.058 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A9. Linear regression models of the proportion of the total number of long, medium, and short silent pauses, by group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values of the pairwise contrasts between the three PPA groups. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA −0.052630769 0.083958973 29 −0.626862948 0.8067 lvPPA–svPPA 0.054213675 0.086555224 29 0.626347813 0.8069 R_NumLongPsil_NumTotPsil nfvPPA–svPPA 0.106844444 0.091712899 29 1.164988195 0.4831 F(2) = 0.679, p = 0.515 lvPPA–nfvPPA 0.044761538 0.069316202 29 0.645758667 0.7962 lvPPA–svPPA −0.067316239 0.071459657 29 −0.942017383 0.6186 R_NumMediumPsil_NumTotPsil nfvPPA–svPPA −0.112077778 0.075717814 29 −1.480203567 0.3150 F(2) = 1.105, p = 0.345 lvPPA–nfvPPA 0.007846154 0.037484946 29 0.209314795 0.9762 lvPPA–svPPA 0.013179487 0.038644088 29 0.341047956 0.9380 R_NumShortPsil_NumTotPsil nfvPPA–svPPA 0.005333333 0.040946822 29 0.13025024 0.9907 F(2) = 0.061, p = 0.941 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A10. Linear regression models of pause frequency (per second of speech/total duration), by type and group. Estimates (B), standard errors (SE(B)), t-values, and p-values. Parameter Contrast B SE(B) t p Intercept (=control) 0.59273 0.06077 9.753 0.0000 *** control–lvPPA lvPPA 0.27727 0.08258 3.358 0.0028 ** F(1) = 11.275, p = 0.003 NumPsil_DurSpeech Intercept (=control) 0.59273 0.06316 9.385 0.0000 *** control–nfvPPA nfvPPA 0.25027 0.09152 2.735 0.0132 * F(1) = 7.478, p = 0.013 Intercept (=control) 0.59273 0.04446 13.331 0.0000 *** control–svPPA svPPA −0.01828 0.06628 −0.276 0.7860 F(1) = 0.076, p = 0.786 Languages 2023, 8, 45 29 of 44 Table A10. Cont. Parameter Contrast B SE(B) t p Intercept (=control) 0.41091 0.0312 13.169 0.0000 *** control–lvPPA lvPPA 0.06524 0.04239 1.539 0.1380 F(1) = 2.368, p = 0.138 NumPsil_DurTot Intercept (=control) 0.410909 0.032833 12.515 0.0000 *** control–nfvPPA nfvPPA −0.003909 0.047579 −0.082 0.9350 F(1) = 0.007, p = 0.935 Intercept (=control) 0.41091 0.02644 15.54 0.0000 *** control–svPPA svPPA −0.02869 0.03942 −0.728 0.4760 F(1) = 0.530, p = 0.476 Intercept (=control) 0.1 0.03459 2.891 0.0085 ** control–lvPPA lvPPA 0.06385 0.047 1.359 0.1881 F(1) = 1.846, p = 0.188 NumPfill_DurSpeech Intercept (=control) 0.1 0.03135 3.19 0.0048 ** control–nfvPPA nfvPPA 0.026 0.04543 0.572 0.5739 F(1) = 0.327, p = 0.574 Intercept (=control) 0.1 0.01504 6.648 0.0000 *** control–svPPA svPPA −0.04 0.02242 −1.784 0.0913 . F(1) = 3.182, p = 0.091 Intercept (=control) 0.07 0.01811 3.866 0.0008 *** control–lvPPA lvPPA 0.01838 0.0246 0.747 0.4628 F(1) = 0.559, p = 0.463 NumPfill_DurTot Intercept (=control) 0.07 0.009966 7.024 0.0000 *** control–nfvPPA nfvPPA −0.018 0.014443 −1.246 0.2280 F(1) = 1.553, p = 0.228 Intercept (=control) 0.07 0.01095 6.391 0.0000 *** control–svPPA svPPA −0.02778 0.01633 −1.701 0.1060 F(1) = 2.894, p = 0.106 Intercept (=control) 0.24909 0.03643 6.838 0.0000 *** control–lvPPA lvPPA 0.03091 0.04949 0.625 0.5390 F(1) = 0.390, p = 0.539 NumSlbLONG_DurSpeech Intercept (=control) 0.249091 0.035233 7.07 0.0000 *** control–nfvPPA nfvPPA −0.007091 0.051058 −0.139 0.8910 F(1) = 0.019, p = 0.891 Intercept (=control) 0.24909 0.03313 7.518 0.0000 *** control–svPPA svPPA −0.0402 0.04939 −0.814 0.4260 F(1) = 0.662, p = 0.426 Intercept (=control) 0.17818 0.02552 6.982 0.0000 *** control–lvPPA lvPPA −0.01587 0.03467 −0.458 0.6520 F(1) = 0.210, p = 0.652 NumSlbLONG_DurTot Intercept (=control) 0.17818 0.02426 7.343 0.0000 *** control–nfvPPA nfvPPA −0.04918 0.03516 −1.399 0.1780 F(1) = 1.956, p = 0.178 Intercept (=control) 0.17818 0.02449 7.277 0.0000 *** control–svPPA svPPA −0.03596 0.0365 −0.985 0.3380 F(1) = 0.970, p = 0.338 Languages 2023, 8, 45 30 of 44 Table A10. Cont. Parameter Contrast B SE(B) t p Intercept (=control) 0.94091 0.08327 11.299 0.0000 *** control–lvPPA lvPPA 0.3714 0.11315 3.282 0.0034 ** F(1) = 10.775, p = 0.003 NumPausesALL_DurSpeech Intercept (=control) 0.94091 0.09101 10.34 0.0000 *** control–nfvPPA nfvPPA 0.26909 0.13189 2.04 0.0555 . F(1) = 4.163, p = 0.055 Intercept (=control) 0.94091 0.06267 15.013 0.0000 *** control–svPPA svPPA −0.09758 0.09343 −1.044 0.3100 F(1) = 1.091, p = 0.310 Intercept (=control) 0.65818 0.048 13.711 0.0000 *** control–lvPPA lvPPA 0.06874 0.06522 1.054 0.3030 F(1) = 1.111, p = 0.303 NumPausesALL_DurTot Intercept (=control) 0.65818 0.05106 12.891 0.0000 *** control–nfvPPA nfvPPA −0.07318 0.07399 −0.989 0.3350 F(1) = 0.978, p = 0.335 Intercept (=control) 0.65818 0.04325 15.218 0.0000 *** control–svPPA svPPA −0.09152 0.06447 −1.419 0.1730 F(1) = 2.015, p = 0.173 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A11. Linear regression models of silent pause frequency (per second of speech/total duration), by length category and group. Estimates (B), standard errors (SE(B)), t-values, and p-values. Parameter Contrast B SE(B) t p Intercept (=control) 0.09355 0.02908 3.217 0.0040 ** control–lvPPA lvPPA 0.13807 0.03951 3.495 0.0021 ** F(1) = 12.215, p = 0.002 NumLongPsil_DurSpeech Intercept (=control) 0.09355 0.06247 1.497 0.1507 control–nfvPPA nfvPPA 0.21775 0.09053 2.405 0.0265 * F(1) = 5.786, p = 0.027 Intercept (=control) 0.09355 0.02936 3.187 0.0051 ** control–svPPA svPPA 0.03945 0.04376 0.902 0.3792 F(1) = 0.813, p = 0.379 Intercept (=control) 0.06182 0.01442 4.286 0.0003 *** control–lvPPA lvPPA 0.06149 0.0196 3.138 0.0048 ** F(1) = 9.847, p = 0.005 NumLongPsil_DurTot Intercept (=control) 0.06182 0.01394 4.436 0.0003 *** control–nfvPPA nfvPPA 0.04948 0.02019 2.45 0.0241 * F(1) = 6.004, p = 0.024 Intercept (=control) 0.06182 0.01453 4.253 0.0005 *** control–svPPA svPPA 0.01618 0.02167 0.747 0.4648 F(1) = 0.558, p = 0.465 Languages 2023, 8, 45 31 of 44 Table A11. Cont. Parameter Contrast B SE(B) t p Intercept (=control) 0.36255 0.04524 8.013 0.0000 *** control–lvPPA lvPPA 0.14822 0.06147 2.411 0.0247 * F(1) = 5.814, p = 0.025 NumMediumPsil_DurSpeech Intercept (=control) 0.36255 0.03624 10.01 0.0000 *** control–nfvPPA nfvPPA 0.07035 0.05251 1.34 0.1960 F(1) = 1.795, p = 0.196 Intercept (=control) 0.36255 0.03524 10.288 0.0000 *** control–svPPA svPPA 0.01445 0.05253 0.275 0.7860 F(1) = 0.076, p = 0.786 Intercept (=control) 0.25236 0.02743 9.201 0.0000 *** control–lvPPA lvPPA 0.03187 0.03727 0.855 0.4020 F(1) = 0.731, p = 0.402 NumMediumPsil_DurTot Intercept (=control) 0.25236 0.03074 8.21 0.0000 *** control–nfvPPA nfvPPA −0.01466 0.04455 −0.329 0.7460 F(1) = 0.108, p = 0.746 Intercept (=control) 0.252364 0.023692 10.652 0.0000 *** control–svPPA svPPA 0.005192 0.035318 0.147 0.8850 F(1) = 0.022, p = 0.885 Intercept (=control) 0.135909 0.026888 5.055 0.0000 *** control–lvPPA lvPPA −0.009986 0.036534 −0.273 0.7870 F(1) = 0.075, p = 0.787 NumShortPsil_DurSpeech Intercept (=control) 0.13591 0.02263 6.006 0.0000 *** control–nfvPPA nfvPPA −0.03761 0.03279 −1.147 0.2660 F(1) = 1.315, p = 0.266 Intercept (=control) 0.13591 0.02211 6.148 0.0000 *** control–svPPA svPPA −0.07069 0.03296 −2.145 0.0459 * F(1) = 4.600, p = 0.046 Intercept (=control) 0.09664 0.01759 5.495 0.0000 *** control–lvPPA lvPPA −0.02794 0.02389 −1.169 0.2550 F(1) = 1.368, p = 0.255 NumShortPsil_DurTot Intercept (=control) 0.09664 0.01688 5.724 0.0000 *** control–nfvPPA nfvPPA −0.04054 0.02446 −1.657 0.1140 F(1) = 2.746, p = 0.114 Intercept (=control) 0.09664 0.01631 5.927 0.0000 *** control–svPPA svPPA −0.04975 0.02431 −2.047 0.0556 . F(1) = 4.189, p = 0.056 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Languages 2023, 8, 45 32 of 44 Table A12. Linear regression models of pause frequency (per second of speech/total duration), by type and group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values of the pairwise contrasts between the three PPA groups. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA 0.027 0.093129414 29 0.289919143 0.9548 lvPPA–svPPA 0.295555556 0.096009242 29 3.078407351 0.0122 * NumPsil_DurSpeech nfvPPA–svPPA 0.268555556 0.101730265 29 2.639878658 0.0343 * F(2) = 5.357, p = 0.010 lvPPA–nfvPPA 0.069153846 0.046411505 29 1.490015171 0.3104 lvPPA–svPPA 0.093931624 0.047846681 29 1.963179515 0.1395 NumPsil_DurTot nfvPPA–svPPA 0.024777778 0.050697781 29 0.488734954 0.8772 F(2) = 2.194, p = 0.130 lvPPA–nfvPPA 0.037846154 0.053692802 29 0.704864575 0.7626 lvPPA–svPPA 0.103846154 0.055353136 29 1.8760663 0.1637 NumPfill_DurSpeech nfvPPA–svPPA 0.066 0.058651533 29 1.125290274 0.5066 F(2) = 1.764, p = 0.189 lvPPA–nfvPPA 0.036384615 0.024079778 29 1.511002967 0.3007 lvPPA–svPPA 0.046162393 0.024824393 29 1.859557777 0.1686 NumPfill_DurTot nfvPPA–svPPA 0.009777778 0.026303635 29 0.37172724 0.9269 F(2) = 2.050, p = 0.147 lvPPA–nfvPPA 0.038 0.056380962 29 0.673986374 0.7803 lvPPA–svPPA 0.071111111 0.058124422 29 1.22342913 0.4493 NumSlbLONG_DurSpeech nfvPPA–svPPA 0.033111111 0.061587955 29 0.537623162 0.8535 F(2) = 0.764, p = 0.475 lvPPA–nfvPPA 0.033307692 0.037724942 29 0.882909051 0.6552 lvPPA–svPPA 0.02008547 0.038891504 29 0.516448782 0.8640 NumSlbLONG_DurTot nfvPPA–svPPA −0.013222222 0.041208981 29 −0.320857779 0.9449 F(2) = 0.402, p = 0.672 lvPPA–nfvPPA 0.102307692 0.136534901 29 0.749315314 0.7364 lvPPA–svPPA 0.468974359 0.14075695 29 3.331802506 0.0065 ** NumPausesALL_DurSpeech nfvPPA–svPPA 0.366666667 0.149144411 29 2.458467358 0.0512 . F(2) = 5.812, p = 0.008 lvPPA–nfvPPA 0.141923077 0.078276391 29 1.813101941 0.1831 lvPPA–svPPA 0.16025641 0.080696921 29 1.985904899 0.1337 NumPausesALL_DurTot nfvPPA–svPPA 0.018333333 0.08550551 29 0.214411135 0.9750 F(2) = 2.551, p = 0.095 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A13. Linear regression models of silent pause frequency (per second of speech/total duration), by length category and group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values of the pairwise contrasts between the three PPA groups. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA −0.079684615 0.079263358 29 −1.00531466 0.5795 lvPPA–svPPA 0.098615385 0.081714407 29 1.20682984 0.4588 NumLongPsil_DurSpeech nfvPPA–svPPA 0.1783 0.086583626 29 2.059280818 0.1163 F(2) = 2.123, p = 0.138 Languages 2023, 8, 45 33 of 44 Table A13. Cont. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA 0.012007692 0.022543868 29 0.532636733 0.8560 lvPPA–svPPA 0.045307692 0.023240989 29 1.949473511 0.1431 NumLongPsil_DurTot nfvPPA–svPPA 0.0333 0.024625879 29 1.352235998 0.3787 F(2) = 1.951, p = 0.160 lvPPA–nfvPPA 0.077869231 0.067193469 29 1.158880944 0.4867 lvPPA–svPPA 0.133769231 0.069271283 29 1.931092153 0.1481 NumMediumPsil_DurSpeech nfvPPA–svPPA 0.0559 0.073399038 29 0.761590365 0.7291 F(2) = 1.937, p = 0.162 lvPPA–nfvPPA 0.046530769 0.048033097 29 0.968723077 0.6021 lvPPA–svPPA 0.026675214 0.049518417 29 0.538692777 0.8530 NumMediumPsil_DurTot nfvPPA–svPPA −0.019855556 0.052469133 29 −0.378423547 0.9243 F(2) = 0.480, p = 0.624 lvPPA–nfvPPA 0.027623077 0.028662036 29 0.9637514 0.6052 lvPPA–svPPA 0.060700855 0.029548348 29 2.054289318 0.1174 NumShortPsil_DurSpeech nfvPPA–svPPA 0.033077778 0.031309082 29 1.056491459 0.5481 F(2) = 2.116, p = 0.139 lvPPA–nfvPPA 0.012592308 0.019018285 29 0.662115821 0.7870 lvPPA–svPPA 0.021803419 0.019606385 29 1.112057049 0.5145 NumShortPsil_DurTot nfvPPA–svPPA 0.009211111 0.020774695 29 0.443381282 0.8977 F(2) = 0.641, p = 0.534 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A14. Linear regression models of pause frequency (per syllable/word), by type and group. Estimates (B), standard errors (SE(B)), t-values, and p-values. Parameter Contrast B SE(B) t p Intercept (=control) 0.1259 0.01624 7.752 0.0000 *** control–lvPPA lvPPA 0.06675 0.02207 3.025 0.0062 ** F(1) = 9.150, p = 0.006 NumPsil_NumTotSlb Intercept (=control) 0.1259 0.01583 7.952 0.0000 *** control–nfvPPA nfvPPA 0.08394 0.02294 3.658 0.0017 ** F(1) = 13.384, p = 0.002 Intercept (=control) 0.1259 0.009674 13.01 0.0000 *** control–svPPA svPPA −0.017445 0.014421 −1.21 0.2420 F(1) = 1.463, p = 0.242 Intercept (=control) 0.21585 0.02503 8.625 0.0000 *** control–lvPPA lvPPA 0.08217 0.034 2.417 0.0244 * F(1) = 5.840, p = 0.024 NumPsil_NumTotWords Intercept (=control) 0.21585 0.02955 7.305 0.0000 *** control–nfvPPA nfvPPA 0.14141 0.04282 3.303 0.0037 ** F(1) = 10.908, p = 0.004 Intercept (=control) 0.21585 0.01634 13.209 0.0000 *** control–svPPA svPPA −0.04357 0.02436 −1.788 0.0906 . F(1) = 3.198, p = 0.091 Languages 2023, 8, 45 34 of 44 Table A14. Cont. Parameter Contrast B SE(B) t p Intercept (=control) 0.021845 0.009658 2.262 0.0339 * control–lvPPA lvPPA 0.016889 0.013123 1.287 0.2115 F(1) = 1.656, p = 0.212 NumPfill_NumTotSlb Intercept (=control) 0.021845 0.006858 3.185 0.0049 ** control–nfvPPA nfvPPA 0.009272 0.009938 0.933 0.3625 F(1) = 0.870, p = 0.363 Intercept (=control) 0.021845 0.003225 6.775 0.0000 *** control–svPPA svPPA −0.010893 0.004807 −2.266 0.0360 * F(1) = 5.135, p = 0.036 Intercept (=control) 0.03732 0.01407 2.653 0.0145 * control–lvPPA lvPPA 0.02144 0.01911 1.122 0.2741 F(1) = 1.258, p = 0.274 NumPfill_NumTotWords Intercept (=control) 0.03732 0.01226 3.043 0.0067 ** control–nfvPPA nfvPPA 0.01651 0.01777 0.929 0.3647 F(1) = 0.863, p = 0.365 Intercept (=control) 0.037317 0.005274 7.076 0.0000 *** control–svPPA svPPA −0.019681 0.007862 −2.503 0.0222 * F(1) = 6.267, p = 0.022 Intercept (=control) 0.053205 0.007982 6.665 0.0000 *** control–lvPPA lvPPA 0.008105 0.010846 0.747 0.4630 F(1) = 0.558, p = 0.463 NumSlbLONG_NumTotSlb Intercept (=control) 0.053205 0.008898 5.979 0.0000 *** control–nfvPPA nfvPPA 0.006629 0.012894 0.514 0.6130 F(1) = 0.264, p = 0.613 Intercept (=control) 0.053205 0.006557 8.115 0.0000 *** control–svPPA svPPA −0.013464 0.009774 −1.378 0.1850 F(1) = 1.898, p = 0.185 Intercept (=control) 0.091492 0.012298 7.44 0.0000 *** control–lvPPA lvPPA 0.002664 0.016709 0.159 0.8750 F(1) = 0.025, p = 0.875 NumSlbLONG_NumTotWords Intercept (=control) 0.091492 0.01513 6.047 0.0000 *** control–nfvPPA nfvPPA 0.008633 0.021925 0.394 0.6980 F(1) = 0.155, p = 0.698 Intercept (=control) 0.09149 0.01124 8.137 0.0000 *** control–svPPA svPPA −0.02835 0.01676 −1.691 0.1080 F(1) = 2.860, p = 0.108 Intercept (=control) 0.20095 0.02555 7.863 0.0000 *** control–lvPPA lvPPA 0.09175 0.03472 2.642 0.0149 * F(1) = 6.982, p = 0.015 NumPausesALL_NumTotSlb Intercept (=control) 0.20095 0.02365 8.496 0.0000 *** control–nfvPPA nfvPPA 0.09984 0.03427 2.913 0.0089 ** F(1) = 8.486, p = 0.009 Intercept (=control) 0.20095 0.01383 14.529 0.0000 *** control–svPPA svPPA −0.0418 0.02062 −2.027 0.0577 . F(1) = 4.111, p = 0.058 Languages 2023, 8, 45 35 of 44 Table A14. Cont. Parameter Contrast B SE(B) t p Intercept (=control) 0.34466 0.03732 9.234 0.0000 *** control–lvPPA lvPPA 0.10628 0.05071 2.096 0.0478 * F(1) = 4.392, p = 0.048 NumPausesALL_NumTotWords Intercept (=control) 0.34466 0.04327 7.966 0.0000 *** control–nfvPPA nfvPPA 0.16656 0.0627 2.656 0.0156 * F(1) = 7.057, p = 0.016 Intercept (=control) 0.34466 0.02368 14.557 0.0000 *** control–svPPA svPPA −0.09159 0.03529 −2.595 0.0183 * F(1) = 6.734, p = 0.018 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A15. Linear regression models of silent pause frequency (per syllable/word), by length category and group. Estimates (B), standard errors (SE(B)), t-values, and p-values. Parameter Contrast B SE(B) t p Intercept (=control) 0.019545 0.006627 2.949 0.0074 ** control–lvPPA lvPPA 0.032455 0.009005 3.604 0.0016 ** F(1) = 12.990, p = 0.002 NumLongPsil_NumTotSlb Intercept (=control) 0.01955 0.01401 1.395 0.1792 control–nfvPPA nfvPPA 0.05525 0.02031 2.721 0.0136 * F(1) = 7.402, p = 0.014 Intercept (=control) 0.019545 0.006086 3.211 0.0048 ** control–svPPA svPPA 0.006788 0.009073 0.748 0.4640 F(1) = 0.560, p = 0.464 Intercept (=control) 0.03318 0.01052 3.154 0.0046 ** control–lvPPA lvPPA 0.04697 0.01429 3.286 0.0034 ** F(1) = 10.799, p = 0.003 NumLongPsil_NumTotWords Intercept (=control) 0.03318 0.02508 1.323 0.2015 control–nfvPPA nfvPPA 0.09632 0.03634 2.651 0.0158 * F(1) = 7.026, p = 0.016 Intercept (=control) 0.033182 0.009454 3.51 0.0025 ** control–svPPA svPPA 0.007485 0.014093 0.531 0.6018 F(1) = 0.282, p = 0.602 Intercept (=control) 0.07727 0.0105 7.362 0.0000 *** control–lvPPA lvPPA 0.03442 0.01426 2.414 0.0246 * F(1) = 5.825, p = 0.025 NumMediumPsil_NumTotSlb Intercept (=control) 0.07727 0.01133 6.821 0.0000 *** control–nfvPPA nfvPPA 0.03323 0.01642 2.024 0.0573 . F(1) = 4.097, p = 0.057 Intercept (=control) 0.077273 0.007192 10.745 0.0000 *** control–svPPA svPPA −0.006939 0.01072 −0.647 0.5260 F(1) = 0.419, p = 0.526 Languages 2023, 8, 45 36 of 44 Table A15. Cont. Parameter Contrast B SE(B) t p Intercept (=control) 0.13264 0.01672 7.932 0.0000 *** control–lvPPA lvPPA 0.04083 0.02272 1.797 0.0861 . F(1) = 3.229, p = 0.086 NumMediumPsil_NumTotWords Intercept (=control) 0.13264 0.01951 6.799 0.0000 *** control–nfvPPA nfvPPA 0.05386 0.02827 1.905 0.0720 . F(1) = 3.630, p = 0.072 Intercept (=control) 0.13264 0.01223 10.845 0.0000 *** control–svPPA svPPA −0.02064 0.01823 −1.132 0.2730 F(1) = 1.281, p = 0.273 Intercept (=control) 0.0291818 0.0061829 4.72 0.0001 *** control–lvPPA lvPPA −0.0003357 0.0084009 −0.04 0.9685 F(1) = 0.002, p = 0.968 NumShortPsil_NumTotSlb Intercept (=control) 0.029182 0.00526 5.548 0.0000 *** control–nfvPPA nfvPPA −0.004382 0.007623 −0.575 0.5720 F(1) = 0.330, p = 0.572 Intercept (=control) 0.029182 0.00473 6.17 0.0000 *** control–svPPA svPPA −0.017182 0.007051 −2.437 0.0254 * F(1) = 5.938, p = 0.025 Intercept (=control) 0.050091 0.009665 5.182 0.0000 *** control–lvPPA lvPPA −0.006168 0.013133 −0.47 0.6430 F(1) = 0.221, p = 0.643 NumShortPsil_NumTotWords Intercept (=control) 0.050091 0.008759 5.719 0.0000 *** control–nfvPPA nfvPPA −0.008791 0.012692 −0.693 0.4970 F(1) = 0.480, p = 0.497 Intercept (=control) 0.050091 0.007997 6.264 0.0000 *** control–svPPA svPPA −0.030424 0.011921 −2.552 0.0200 * F(1) = 6.513, p = 0.020 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A16. Linear regression models of pause frequency (per syllable/word), by type and group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values of the pairwise contrasts between the three PPA groups. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA −0.017188314 0.024675406 29 −0.6965767660.7674 lvPPA–svPPA 0.084197561 0.02543844 29 3.309855526 0.0069 ** NumPsil_NumTotSlb nfvPPA–svPPA 0.101385875 0.026954272 29 3.761402818 0.0021 ** F(2) = 8.140, p = 0.002 lvPPA–nfvPPA −0.059240685 0.041933904 29 −1.4127156910.3477 lvPPA–svPPA 0.12573904 0.04323062 29 2.90856432 0.0184 * NumPsil_NumTotWords nfvPPA–svPPA 0.184979724 0.045806658 29 4.038271597 0.0010 ** F(2) = 8.467, p = 0.001 lvPPA–nfvPPA 0.007616662 0.013685029 29 0.556568905 0.8439 lvPPA–svPPA 0.027781261 0.014108209 29 1.969155704 0.1380 NumPfill_NumTotSlb nfvPPA–svPPA 0.020164599 0.014948893 29 1.348902509 0.3804 F(2) = 1.984, p = 0.156 Languages 2023, 8, 45 37 of 44 Table A16. Cont. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA 0.00493464 0.021348837 29 0.231143252 0.9710 lvPPA–svPPA 0.04112329 0.022009004 29 1.868475768 0.1660 NumPfill_NumTotWords nfvPPA–svPPA 0.036188651 0.023320482 29 1.551796862 0.2824 F(2) = 1.934, p = 0.163 lvPPA–nfvPPA 0.001475497 0.012940583 29 0.114020924 0.9929 lvPPA–svPPA 0.021568754 0.013340743 29 1.616758051 0.2548 NumSlbLONG_NumTotSlb nfvPPA–svPPA 0.020093256 0.014135695 29 1.421455185 0.3434 F(2) = 1.503, p = 0.239 lvPPA–nfvPPA −0.0059695 0.020561471 29 −0.2903245680.9547 lvPPA–svPPA 0.031009914 0.02119729 29 1.462918756 0.3232 NumSlbLONG_NumTotWords nfvPPA–svPPA 0.036979414 0.0224604 29 1.646427221 0.2429 F(2) = 1.571, p = 0.225 lvPPA–nfvPPA −0.008096155 0.038642381 29 −0.2095149180.9761 lvPPA–svPPA 0.133547575 0.039837314 29 3.352323788 0.0062 ** NumPausesALL_NumTotSlb nfvPPA–svPPA 0.141643731 0.04221115 29 3.355599894 0.0061 ** F(2) = 7.222, p = 0.003 lvPPA–nfvPPA −0.060275545 0.062779733 29 −0.9601115230.6074 lvPPA–svPPA 0.197872244 0.064721062 29 3.057308376 0.0128 * NumPausesALL_NumTotWords nfvPPA–svPPA 0.258147789 0.068577677 29 3.764312249 0.0021 ** F(2) = 7.751, p = 0.002 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A17. Linear regression models of silent pause frequency (per syllable/word), by length category and group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values of the pairwise contrasts between the three PPA groups. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA −0.0228 0.018015207 29 −1.26559743 0.4255 lvPPA–svPPA 0.025666667 0.018572289 29 1.381987262 0.3633 NumLongPsil_NumTotSlb nfvPPA–svPPA 0.048466667 0.019678979 29 2.462864876 0.0507 . F(2) = 3.033, p = 0.064 lvPPA–nfvPPA −0.049346154 0.031119401 29 −1.5857038710.2678 lvPPA–svPPA 0.039487179 0.032081701 29 1.230831845 0.4451 NumLongPsil_NumTotWords nfvPPA–svPPA 0.088833333 0.033993394 29 2.613252849 0.0364 * F(2) = 3.452, p = 0.045 lvPPA–nfvPPA 0.001192308 0.017196672 29 0.069333631 0.9974 lvPPA–svPPA 0.041358974 0.017728442 29 2.332916497 0.0670 . NumMediumPsil_NumTotSlb nfvPPA–svPPA 0.040166667 0.018784849 29 2.138248075 0.0996 . F(2) = 3.230, p = 0.054 lvPPA–nfvPPA −0.013038462 0.02842212 29 −0.45874345 0.8909 lvPPA–svPPA 0.061461538 0.029301013 29 2.097590876 0.1079 NumMediumPsil_NumTotWords nfvPPA–svPPA 0.0745 0.03104701 29 2.399586969 0.0582 . F(2) = 3.298, p = 0.051 lvPPA–nfvPPA 0.004046154 0.006866938 29 0.589222447 0.8269 lvPPA–svPPA 0.016846154 0.007079283 29 2.379641236 0.0607 . NumShortPsil_NumTotSlb nfvPPA–svPPA 0.0128 0.007501125 29 1.706410666 0.2200 F(2) = 2.936, p = 0.069 Languages 2023, 8, 45 38 of 44 Table A17. Cont. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA 0.002623077 0.010439284 29 0.251269806 0.9658 lvPPA–svPPA 0.02425641 0.010762097 29 2.253874028 0.0789 . NumShortPsil_NumTotWords nfvPPA–svPPA 0.021633333 0.011403391 29 1.897096469 0.1576 F(2) = 2.837, p = 0.075 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Table A18. Linear regression models of pause–speech and pause–total duration ratios, by type and group. Estimates (B), standard errors (SE(B)), t-values, and p-values. Parameter Contrast B SE(B) t p Intercept (=control) 37.268 6.383 5.839 0.0000 *** control–lvPPA lvPPA 35.33 8.673 4.074 0.0005 *** F(1) = 16.594, p = 0.001 R_DurPsil_DurSpeech Intercept (=control) 37.27 31.22 1.194 0.2473 control–nfvPPA nfvPPA 95.87 45.25 2.119 0.0475 * F(1) = 4.490, p = 0.048 Intercept (=control) 37.268 7.362 5.062 0.0001 *** control–svPPA svPPA 12.322 10.975 1.123 0.2760 F(1) = 1.261, p = 0.276 Intercept (=control) 25.095 2.538 9.887 0.0000 *** control–lvPPA lvPPA 13.773 3.448 3.994 0.0006 *** F(1) = 15.952, p = 0.001 R_DurPsil_DurTot Intercept (=control) 25.095 4.602 5.453 0.0000 *** control–nfvPPA nfvPPA 18.874 6.669 2.83 0.0107 * F(1) = 8.010, p = 0.011 Intercept (=control) 25.095 3.175 7.904 0.0000 *** control–svPPA svPPA 5.259 4.733 1.111 0.2810 F(1) = 1.235, p = 0.281 Intercept (=control) 6.436 2.431 2.648 0.0147 * control–lvPPA lvPPA 3.417 3.302 1.035 0.3120 F(1) = 1.071, p = 0.312 R_DurPfill_DurSpeech Intercept (=control) 6.436 2.822 2.281 0.0343 * control–nfvPPA nfvPPA 2.303 4.09 0.563 0.5800 F(1) = 0.317, p = 0.580 Intercept (=control) 6.4364 0.8877 7.25 0.0000 *** control–svPPA svPPA −3.6941 1.3234 −2.791 0.0121 * F(1) = 7.792, p = 0.012 Intercept (=control) 4.5091 1.1903 3.788 0.0010 ** control–lvPPA lvPPA 0.6932 1.6174 0.429 0.6724 F(1) = 0.184, p = 0.672 R_DurPfill_DurTot Intercept (=control) 4.5091 0.7249 6.22 0.0000 *** control–nfvPPA nfvPPA −1.1811 1.0505 −1.124 0.2750 F(1) = 1.264, p = 0.275 Intercept (=control) 4.5091 0.6087 7.408 0.0000 *** control–svPPA svPPA −2.5035 0.9074 −2.759 0.0129 * F(1) = 7.612, p = 0.013 Languages 2023, 8, 45 39 of 44 Table A18. Cont. Parameter Contrast B SE(B) t p Intercept (=control) 14.441 2.025 7.131 0.0000 *** control–lvPPA lvPPA 1.742 2.752 0.633 0.5330 F(1) = 0.401, p = 0.533 R_DurSlbLONG_DurSpeech Intercept (=control) 14.441 2.139 6.752 0.0000 *** control–nfvPPA nfvPPA 1.078 3.099 0.348 0.7320 F(1) = 0.121, p = 0.732 Intercept (=control) 14.441 1.868 7.73 0.0000 *** control–svPPA svPPA −3.591 2.785 −1.289 0.2140 F(1) = 1.662, p = 0.214 Intercept (=control) 10.345 1.399 7.397 0.0000 *** control–lvPPA lvPPA −1.151 1.9 −0.606 0.5510 F(1) = 0.367, p = 0.551 R_DurSlbLONG_DurTot Intercept (=control) 10.345 1.554 6.659 0.0000 *** control–nfvPPA nfvPPA −1.982 2.251 −0.88 0.3900 F(1) = 0.775, p = 0.390 Intercept (=control) 10.345 1.413 7.324 0.0000 *** control–svPPA svPPA −2.909 2.106 −1.382 0.1840 F(1) = 1.909, p = 0.184 Intercept (=control) 58.145 6.494 8.953 0.0000 *** control–lvPPA lvPPA 40.49 8.824 4.589 0.0001 *** F(1) = 21.055, p = 0.000 R_DurPausesALL_DurSpeech Intercept (=control) 58.14 32.47 1.791 0.0893 . control–nfvPPA nfvPPA 99.25 47.05 2.109 0.0484 * F(1) = 4.450, p = 0.048 Intercept (=control) 58.145 6.762 8.599 0.0000 *** control–svPPA svPPA 5.039 10.08 0.5 0.6230 F(1) = 0.250, p = 0.623 Intercept (=control) 39.949 2.047 19.518 0.0000 *** control–lvPPA lvPPA 13.313 2.781 4.787 0.0001 *** F(1) = 22.917, p = 0.000 R_DurPausesALL_DurTot Intercept (=control) 39.949 3.912 10.211 0.0000 *** control–nfvPPA nfvPPA 15.712 5.67 2.771 0.0122 * F(1) = 7.680, p = 0.012 Intercept (=control) 39.9491 2.6212 15.241 0.0000 *** control–svPPA svPPA −0.1524 3.9074 −0.039 0.9690 F(1) = 0.002, p = 0.969 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Languages 2023, 8, 45 40 of 44 Table A19. Linear regression models of pause–speech and pause–total duration ratios, by type and group. Estimates (B), standard errors (SE(B)), degrees of freedom (df), t-values, and p-values of the pairwise contrasts between the three PPA groups. Parameter Contrast B SE(B) df t p lvPPA–nfvPPA −60.54253846 36.2992659 29 −1.667872255 0.2345 lvPPA–svPPA 23.00846154 37.42174282 29 0.614842062 0.8132 R_DurPsil_DurSpeech nfvPPA–svPPA 83.551 39.65163922 29 2.107126001 0.1059 F(2) = 2.448, p = 0.104 lvPPA–nfvPPA −5.101307692 6.0224746 29 −0.847045115 0.6773 lvPPA–svPPA 8.514358974 6.208706707 29 1.371357897 0.3687 R_DurPsil_DurTot nfvPPA–svPPA 13.61566667 6.578672714 29 2.069667737 0.1140 F(2) = 2.176, p = 0.132 lvPPA–nfvPPA 1.114846154 4.218931148 29 0.264248483 0.9623 lvPPA–svPPA 7.111623932 4.349392543 29 1.635084408 0.2474 R_DurPfill_DurSpeech nfvPPA–svPPA 5.996777778 4.60856526 29 1.301224446 0.4059 F(2) = 1.447, p = 0.252 lvPPA–nfvPPA 1.874307692 1.539023641 29 1.217855037 0.4524 lvPPA–svPPA 3.196752137 1.586614645 29 2.01482581 0.1266 R_DurPfill_DurTot nfvPPA–svPPA 1.322444444 1.681158245 29 0.786626987 0.7141 F(2) = 2.112, p = 0.139 lvPPA–nfvPPA 0.664361538 3.113531785 29 0.213378756 0.9752 lvPPA–svPPA 5.332683761 3.209811076 29 1.661369979 0.2370 R_DurSlbLONG_DurSpeech nfvPPA–svPPA 4.668322222 3.401078121 29 1.372600704 0.3681 F(2) = 1.524, p = 0.235 lvPPA–nfvPPA 0.831038462 2.134732906 29 0.389293883 0.9201 lvPPA–svPPA 1.75842735 2.200744941 29 0.799014605 0.7066 R_DurSlbLONG_DurTot nfvPPA–svPPA 0.927388889 2.331883495 29 0.397699495 0.9168 F(2) = 0.321, p = 0.728 lvPPA–nfvPPA −58.76338462 37.70476862 29 −1.558513333 0.2795 lvPPA–svPPA 35.45128205 38.8707077 29 0.912030785 0.6372 R_DurPausesALL_DurSpeech nfvPPA–svPPA 94.21466667 41.18694539 29 2.287488566 0.0736 . F(2) = 2.712, p = 0.083 lvPPA–nfvPPA −2.398692308 5.191833083 29 −0.462012601 0.8894 lvPPA–svPPA 13.46564103 5.352379383 29 2.515823349 0.0452 * R_DurPausesALL_DurTot nfvPPA–svPPA 15.86433333 5.671318337 29 2.797291986 0.0239 * F(2) = 4.575, p = 0.019 Note: Significance codes: ‘***’ refers to p < 0.001; ‘**’ refers to p < 0.01; ‘*’ refers to p < 0.05; ‘.’ refers to p < 0.1; ‘ ’ refers to p < 1. Note 1 Note that the last available public report on language use in Catalonia (Direcció General de Política Lingüística de la Generalitat de Catalunya 2019) showed that 97% of the population over the age of 15 say that they are proficient in understanding, speaking, reading, and writing in Spanish (in Catalan: 94%, 81.2%, 85.5%, and 65.3%, respectively), and that 94.2% use Spanish on a daily basis. 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