The role of silent pauses in speech pathology

Οι παύσεις στον προφορικό λόγο θεωρούνται ένα στοιχείο χρονικής οργάνωσης της ομιλίας καθώς και μία ένδειξη γνωστικών διεργασιών, όπως επιλογή και ανάσυρση της λέξης, οργάνωση της δομής αλλά και της άρθρωσης του λόγου καθώς και μνημονικών διεργασιών. Μελέτες υποστηρίζουν ότι οι παύσεις στον φυσιολογικό λόγο κατανέμονται με συγκεκριμένο τρόπο, σχηματίζοντας διακριτά πρότυπα, ωστόσο τα αντίστοιχα ευρήματα σε παθολογικούς πληθυσμούς και κυρίως σε ασθενείς με αφασία μετά από ΑΕΕ στο αριστερό ημισφαίριο είναι λιγοστά και περιορίζονται σε μικρό αριθμό ασθενών. Η παρούσα μελέτη στοχεύει πρώτον στη διερεύνηση των προτύπων που σχηματίζουν οι σιωπηλές παύσεις στην αυθόρμητη ομιλία ασθενών με αφασία μετά από αριστερό ΑΕΕ, σε σύγκριση με τα πρότυπα που εμφανίζονται στο λόγο των φυσιολογικών ομιλητών, δεύτερον στη διερεύνηση ύπαρξης διαφορετικών προτύπων των παύσεων μεταξύ των ασθενών και τέλος στη μελέτη πιθανών συσχετίσεων μεταξύ των χαρακτηριστικών των παύσεων και των εγκεφαλικών βλαβών σε συγκεκριμένες περιοχές του εγκέφαλου στους ασθενείς με αφασία. Τα αποτελέσματά μας επιβεβαιώνουν την ύπαρξη διαφορετικών κατανομών των παύσεων στον αυθόρμητο λόγο φυσιολογικών ομιλητών και ομιλητών με αφασία. Επιπρόσθετα, η διερεύνηση των κατανομών των παύσεων στην ομάδα των ασθενών αποκαλύπτει διαφορετικά πρότυπα κατανομών μεταξύ των ασθενών, πρότυπα τα οποία φαίνεται να συσχετίζονται με τη θέση και την έκταση της εγκεφαλικής βλάβης στο αριστερό ημισφαίριο των ασθενών. Συνοψίζοντας, τα ευρήματά μας υποδεικνύουν τη σημασία του ρόλου των παύσεων στην αυθόρμητη ομιλία τόσο κλινικών ομάδων, ως ένα διακριτό στοιχείο του προφορικού λόγου, όσο και στην φυσιολογική ομιλία.Pauses may be studied as an aspect of the temporal organization of speech, as well as an index of internal cognitive processes, like word selection and retrieval, monitoring, articulatory planning, and memory. There are studies demonstrating a specific pattern of pauses in normal speech, however evidence from pathological populations, and especially aphasia patients is sparse and restricted to small scale studies. The aim of the present study is threefold. First, to investigate possibly different patterns of pause distribution between healthy speakers and aphasics. Second, to examine distinct pause trends among individual patients. Third, to scrutinize possible associations between aphasic pause preferences and lesion characteristics. Our results indicate different distribution of pauses during connected speech between controls and aphasics. Moreover, different pause profiles are revealed when assessing individual patient data. Finally, these profiles seem to be related to indices of lesion extent and locus. Overall, our findings stress the importance of pauses as an integral part of language assessment in clinical populations, and further support their role in healthy language production as well as impaired speech output

Prosodic and Segmental Correlates of Spontaneous Dutch Speech in Patients with Parkinson’s Disease:A Pilot Study

This study investigates the acoustic correlates of prosody and vowel articulation in Dutch individuals with Parkinson’s Disease (PD). We compared prosodic and segmental acoustic measures in spontaneous monologues in PD patients to those in elderly healthy controls matched for age and gender. For the prosodic measurements of pitch variability, span and speech rate, we analysed fundamental frequency and intensity. For articulation measurements, the first two formants were calculated from Dutch corner vowels extracted from the speech signal. Results show a monopitch trend, reduced speech rate, centralization of the formant frequencies and reduced first formant variability in individuals with PD compared to control group

Cognivitra, a digital solution to support dual-task rehabilitation training

This article focuses on an eHealth application, CogniViTra, to support cognitive and physical training (i.e., dual-task training), which can be done at home with supervision of a health care provider. CogniViTra was designed and implemented to take advantage of an existing Platform of Services supporting a Cognitive Health Ecosystem and comprises several components, including the CogniViTra Box (i.e., the patient terminal equipment), the Virtual Coach to provide assistance, the Game Presentation for the rehabilitation exercises, and the Pose and Gesture Recognition to quantify responses during dual-task training. In terms of validation, a functional prototype was exposed in a highly specialized event related to healthy and active ageing, and key stakeholders were invited to test it and share their insights. Fifty-seven specialists in information-technology-based applications to support healthy and active ageing were involved and the results and indicated that the functional prototype presents good performance in recognizing poses and gestures such as moving the trunk to the left or to the right, and that most of the participants would use or suggest the utilization of CogniViTra. In general, participants considered that CogniViTra is a useful tool and may represent an added value for remote dual-task training.This study has received funding from the European Union under the AAL programme through project CogniViTra (Grant No. AAL-2018-5-115-CP), with national funding support from FCT, ISCIII, and FNR. This presentation reflects the authors’ views, and neither AAL nor the National Funding Agencies are responsible for any use that may be made of the information

VOCAL BIOMARKERS OF CLINICAL DEPRESSION: WORKING TOWARDS AN INTEGRATED MODEL OF DEPRESSION AND SPEECH

Speech output has long been considered a sensitive marker of a person’s mental state. It has been previously examined as a possible biomarker for diagnosis and treatment response for certain mental health conditions, including clinical depression. To date, it has been difficult to draw robust conclusions from past results due to diversity in samples, speech material, investigated parameters, and analytical methods. Within this exploratory study of speech in clinically depressed individuals, articulatory and phonatory behaviours are examined in relation to psychomotor symptom profiles and overall symptom severity. A systematic review provided context from the existing body of knowledge on the effects of depression on speech, and provided context for experimental setup within this body of work. Examinations of vowel space, monophthong, and diphthong productions as well as a multivariate acoustic analysis of other speech parameters (e.g., F0 range, perturbation measures, composite measures, etc.) are undertaken with the goal of creating a working model of the effects of depression on speech. Initial results demonstrate that overall vowel space area was not different between depressed and healthy speakers, but on closer inspection, this was due to more specific deficits seen in depressed patients along the first formant (F1) axis. Speakers with depression were more likely to produce centralised vowels along F1, as compared to F2—and this was more pronounced for low-front vowels, which are more complex given the degree of tongue-jaw coupling required for production. This pattern was seen in both monophthong and diphthong productions. Other articulatory and phonatory measures were inspected in a factor analysis as well, suggesting additional vocal biomarkers for consideration in diagnosis and treatment assessment of depression—including aperiodicity measures (e.g., higher shimmer and jitter), changes in spectral slope and tilt, and additive noise measures such as increased harmonics-to-noise ratio. Intonation was also affected by diagnostic status, but only for specific speech tasks. These results suggest that laryngeal and articulatory control is reduced by depression. Findings support the clinical utility of combining Ellgring and Scherer’s (1996) psychomotor retardation and social-emotional hypotheses to explain the effects of depression on speech, which suggest observed changes are due to a combination of cognitive, psycho-physiological and motoric mechanisms. Ultimately, depressive speech is able to be modelled along a continuum of hypo- to hyper-speech, where depressed individuals are able to assess communicative situations, assess speech requirements, and then engage in the minimum amount of motoric output necessary to convey their message. As speakers fluctuate with depressive symptoms throughout the course of their disorder, they move along the hypo-hyper-speech continuum and their speech is impacted accordingly. Recommendations for future clinical investigations of the effects of depression on speech are also presented, including suggestions for recording and reporting standards. Results contribute towards cross-disciplinary research into speech analysis between the fields of psychiatry, computer science, and speech science

The analysis of breathing and rhythm in speech

Speech rhythm can be described as the temporal patterning by which speech events, such as vocalic onsets, occur. Despite efforts to quantify and model speech rhythm across languages, it remains a scientifically enigmatic aspect of prosody. For instance, one challenge lies in determining how to best quantify and analyse speech rhythm. Techniques range from manual phonetic annotation to the automatic extraction of acoustic features. It is currently unclear how closely these differing approaches correspond to one another. Moreover, the primary means of speech rhythm research has been the analysis of the acoustic signal only. Investigations of speech rhythm may instead benefit from a range of complementary measures, including physiological recordings, such as of respiratory effort. This thesis therefore combines acoustic recording with inductive plethysmography (breath belts) to capture temporal characteristics of speech and speech breathing rhythms. The first part examines the performance of existing phonetic and algorithmic techniques for acoustic prosodic analysis in a new corpus of rhythmically diverse English and Mandarin speech. The second part addresses the need for an automatic speech breathing annotation technique by developing a novel function that is robust to the noisy plethysmography typical of spontaneous, naturalistic speech production. These methods are then applied in the following section to the analysis of English speech and speech breathing in a second, larger corpus. Finally, behavioural experiments were conducted to investigate listeners' perception of speech breathing using a novel gap detection task. The thesis establishes the feasibility, as well as limits, of automatic methods in comparison to manual annotation. In the speech breathing corpus analysis, they help show that speakers maintain a normative, yet contextually adaptive breathing style during speech. The perception experiments in turn demonstrate that listeners are sensitive to the violation of these speech breathing norms, even if unconsciously so. The thesis concludes by underscoring breathing as a necessary, yet often overlooked, component in speech rhythm planning and production

Weight perception during action observation: the role of motor skills and abilities

The aim of this work is to investigate the role that motor skills and abilities have in perceiving the weight of an object handled and moved by another person. This topic provides an understanding of the interaction between actions and perceptions by assessing how motor repertoire, either shaped during years of sport practice, or altered during aging and fatigability, modulates the way individuals perceived the movement performed by others. The first chapter (Chapter 1) presents a summary of the scientific literature about this topic, and, in particular, of the mechanisms underlying it, primarily motor resonance. Next, the state of the art on the perception of the weight of an object during the execution and observation of a movement is presented. The first study (Chapter 2) investigates the role of motor expertise and the acquisition of specific skills in assessing the weight of an object moved during a sport-specific gesture. In the second study (Chapter 3), the role of ageing and the decline of motor ability in the ability to perceive the weight of an object during the observation of an everyday life movement was investigated. In the third study (Chapter 4), the focus was on how the nature of the movement, i.e. concentric or eccentric movement, affected the ability to discriminate the weight of an object during action observation. The fourth study (Chapter 5) focused on how the state of the observer could affect this ability, specifically how fatigue affects the ability to discriminate and evaluate the weight of an object during the observation of an everyday movement

Linguistic- and Acoustic-based Automatic Dementia Detection using Deep Learning Methods

Dementia can affect a person's speech and language abilities, even in the early stages. Dementia is incurable, but early detection can enable treatment that can slow down and maintain mental function. Therefore, early diagnosis of dementia is of great importance. However, current dementia detection procedures in clinical practice are expensive, invasive, and sometimes inaccurate. In comparison, computational tools based on the automatic analysis of spoken language have the potential to be applied as a cheap, easy-to-use, and objective clinical assistance tool for dementia detection. In recent years, several studies have shown promise in this area. However, most studies focus heavily on the machine learning aspects and, as a consequence, often lack sufficient incorporation of clinical knowledge. Many studies also concentrate on clinically less relevant tasks such as the distinction between HC and people with AD which is relatively easy and therefore less interesting both in terms of the machine learning and the clinical application. The studies in this thesis concentrate on automatically identifying signs of neurodegenerative dementia in the early stages and distinguishing them from other clinical, diagnostic categories related to memory problems: (FMD, MCI, and HC). A key focus, when designing the proposed systems has been to better consider (and incorporate) currently used clinical knowledge and also to bear in mind how these machine-learning based systems could be translated for use in real clinical settings. Firstly, a state-of-the-art end-to-end system is constructed for extracting linguistic information from automatically transcribed spontaneous speech. The system's architecture is based on hierarchical principles thereby mimicking those used in clinical practice where information at both word-, sentence- and paragraph-level is used when extracting information to be used for diagnosis. Secondly, hand-crafted features are designed that are based on clinical knowledge of the importance of pausing and rhythm. These are successfully joined with features extracted from the end-to-end system. Thirdly, different classification tasks are explored, each set up so as to represent the types of diagnostic decision-making that is relevant in clinical practice. Finally, experiments are conducted to explore how to better deal with the known problem of confounding and overlapping symptoms on speech and language from age and cognitive decline. A multi-task system is constructed that takes age into account while predicting cognitive decline. The studies use the publicly available DementiaBank dataset as well as the IVA dataset, which has been collected by our collaborators at the Royal Hallamshire Hospital, UK. In conclusion, this thesis proposes multiple methods of using speech and language information for dementia detection with state-of-the-art deep learning technologies, confirming the automatic system's potential for dementia detection

Visual-Vestibular Integration During Self-Motion Perception in Younger and Older Adults

Younger adults integrate visual and vestibular cues to self-motion in a manner consistent with optimal integration; however, little is currently known about whether this process changes with older age. Our objective was to determine whether older adults, like younger adults, display evidence of optimal visual-vestibular integration, including reductions in bimodal variance (visual-vestibular) compared with unimodal variance (visual or vestibular alone), and reliability-based cue weighting. We used a motion simulator and a head-mounted display to introduce a 2-interval forced-choice heading estimation task. Older (65+ years) and younger adults (18–35 years) judged which of two movements was more rightward. Movements consisted of vestibular cues (passive movement in darkness), visual cues (optic flow), or both cues combined. The combined condition contained either congruent cues or incongruent cues (either a subtle 5° or larger 20° conflict). Results demonstrated that older adults had less reliable visual heading estimates than younger adults but comparable vestibular heading estimates. During combined, congruent conditions, both age groups exhibited reductions in combined variance, consistent with predicted optimal integration. During subtle cue conflicts, only younger adults exhibited combined variance consistent with predicted optimal integration, but both age groups displayed reliability-based cue weighting. During larger spatial conflicts, neither group demonstrated optimal reductions in variance. Younger adults displayed reliability-based cue weighting but older adults’ heading estimates were biased toward the less reliable visual estimate. Older adults’ tendency to incorporate spatially conflicting and unreliable visual cues into their self-motion percept may affect their performance on mobility-related tasks like walking and driving