Prosodic abnormalities in schizotypal personality disorder

The contribution of prosody to machine classification of schizophrenia

We show how acoustic prosodic features, such as pitch and gaps, can be used computationally for detecting symptoms of schizophrenia from a single spoken response. We compare the individual contributions of acoustic and previously-employed text modalities to the algorithmic determination whether the speaker has schizophrenia. Our classification results clearly show that we can extract relevant acoustic features better than those textual ones. We find that, when combined with those acoustic features, textual features improve classification only slightly.

Automated analysis of speech as a marker of sub-clinical psychotic experiences

Automated speech analysis techniques, when combined with artificial intelligence and machine learning, show potential in capturing and predicting a wide range of psychosis symptoms, garnering attention from researchers. These techniques hold promise in predicting the transition to clinical psychosis from at-risk states, as well as relapse or treatment response in individuals with clinical-level psychosis. However, challenges in scientific validation hinder the translation of these techniques into practical applications. Although sub-clinical research could aid to tackle most of these challenges, there have been only few studies conducted in speech and psychosis research in non-clinical populations. This work aims to facilitate this work by summarizing automated speech analytical concepts and the intersection of this field with psychosis research. We review psychosis continuum and sub-clinical psychotic experiences, and the benefits of researching them. Then, we discuss the connection between speech and psychotic symptoms. Thirdly, we overview current and state-of-the art approaches to the automated analysis of speech both in terms of language use (text-based analysis) and vocal features (audio-based analysis). Then, we review techniques applied in subclinical population and findings in these samples. Finally, we discuss research challenges in the field, recommend future research endeavors and outline how research in subclinical populations can tackle the listed challenges.

Prosody and schizophrenia. Objective acoustic measurements of monotonous and flat intonation in young Danish people with a schizophrenia diagnosis. A pilot study

PURPOSE

Patients with schizophrenia have a flat and monotonous intonation. The purpose of the study was to find the variables of flat speech that differed in patients from those in healthy controls in Danish.

MATERIALS AND METHODS

We compared drug-naïve schizophrenic patients 5 men, 13 women and 18 controls, aged 18-35 years, which had all grown up in Copenhagen speaking modern Danish standard (rigsdansk). We used two different tasks that lay different demands on the speaker to elicit spontaneous speech: a retelling of a film clip and telling a story from pictures in a book. A linguist used the computer program Praat to extract the phonetic linguistic parameters.

RESULTS

We found different results for the two elicitation tasks (Task 1: a retelling of a film clip, task 2: telling a story from pictures in a book). There was higher intensity variation in task one in controls and higher pitch variation in task two in controls. We found a difference in intensity with higher intensity variation in the stresses in the controls in task one and fewer syllables between each stress in the controls. We also found higher F1 variation in task one and two in the patient group and higher F2 variation in the control group in both tasks.

CONCLUSIONS

The results varied between patients and controls, but the demands also made a difference. Further research is needed to elucidate the possibilities of acoustic measures in diagnostics or linguistic treatment related to schizophrenia.

Markers of schizophrenia at the prosody/pragmatics interface. Evidence from corpora of spontaneous speech interactions

The speech of individuals with schizophrenia exhibits atypical prosody and pragmatic dysfunctions, producing monotony. The paper presents the outcomes of corpus-based research on the prosodic features of the pathology as they manifest in real-life spontaneous interactions. The research relies on a corpus of schizophrenic speech recorded during psychiatric interviews (CIPPS) compared to a sampling of non-pathological speech derived from the LABLITA corpus of spoken Italian, which has been selected according to comparability requirements. Corpora has been intensively analyzed in the Language into Act Theory (L-AcT) frame, which links prosodic cues and pragmatic values. A cluster of linguistic parameters marked by prosody has been considered: utterance boundaries, information structure, speech disfluency, and prosodic prominence. The speech flow of patients turns out to be organized into small chunks of information that are shorter and scarcely structured, with an atypical proportion of post-nuclear information units (Appendix). It is pervasively scattered with silences, especially with long pauses between utterances and long silences at turn-taking. Fluency is hindered by retracing phenomena that characterize complex information structures. The acoustic parameters that give rise to prosodic prominence (f0 mean, f0 standard deviation, spectral emphasis, and intensity variation) have been measured considering the pragmatic roles of the prosodic units, distinguishing prominences within the illocutionary units (Comment) from those characterizing Topic units. Patients show a flattening of the Comment-prominence, reflecting impairments in performing the illocutionary activity. Reduced values of spectral emphasis and intensity variation also suggest a lack of engagement in communication. Conversely, Topic-prominence shows higher values for f0 standard deviation and spectral emphasis, suggesting effort when defining the domain of relevance of the illocutionary force. When comparing Topic and Comment-prominences of patients, the former consistently exhibit higher values across all parameters. In contrast, the non-pathological group displays the opposite pattern.

Online speech assessment of the psychotic spectrum: Exploring the relationship between overlapping acoustic markers of schizotypy, depression and anxiety

BACKGROUND

Remote assessment of acoustic alterations in speech holds promise to increase scalability and validity in research across the psychosis spectrum. A feasible first step in establishing a procedure for online assessments is to assess acoustic alterations in psychometric schizotypy. However, to date, the complex relationship between alterations in speech related to schizotypy and those related to comorbid conditions such as symptoms of depression and anxiety has not been investigated. This study tested whether (1) depression, generalized anxiety and high psychometric schizotypy have similar voice characteristics, (2) which acoustic markers of online collected speech are the strongest predictors of psychometric schizotypy, (3) whether including generalized anxiety and depression symptoms in the model can improve the prediction of schizotypy.

METHODS

We collected cross-sectional, online-recorded speech data from 441 participants, assessing demographics, symptoms of depression, generalized anxiety and psychometric schizotypy.

RESULTS

Speech samples collected online could predict psychometric schizotypy, depression, and anxiety symptoms with weak to moderate predictive power, and with moderate and good predictive power when basic demographic variables were added to the models. Most influential features of these models largely overlapped. The predictive power of speech marker-based models of schizotypy significantly improved after including symptom scores of depression and generalized anxiety in the models (from R2 = 0.296 to R2 = 0. 436).

CONCLUSIONS

Acoustic features of online collected speech are predictive of psychometric schizotypy as well as generalized anxiety and depression symptoms. The acoustic characteristics of schizotypy, depression and anxiety symptoms significantly overlap. Speech models that are designed to predict schizotypy or symptoms of the schizophrenia spectrum might therefore benefit from controlling for symptoms of depression and anxiety.

A Narrative Review of Speech and EEG Features for Schizophrenia Detection: Progress and Challenges

Schizophrenia is a mental illness that affects an estimated 21 million people worldwide. The literature establishes that electroencephalography (EEG) is a well-implemented means of studying and diagnosing mental disorders. However, it is known that speech and language provide unique and essential information about human thought. Semantic and emotional content, semantic coherence, syntactic structure, and complexity can thus be combined in a machine learning process to detect schizophrenia. Several studies show that early identification is crucial to prevent the onset of illness or mitigate possible complications. Therefore, it is necessary to identify disease-specific biomarkers for an early diagnosis support system. This work contributes to improving our knowledge about schizophrenia and the features that can identify this mental illness via speech and EEG. The emotional state is a specific characteristic of schizophrenia that can be identified with speech emotion analysis. The most used features of speech found in the literature review are fundamental frequency (F0), intensity/loudness (I), frequency formants (F1, F2, and F3), Mel-frequency cepstral coefficients (MFCC's), the duration of pauses and sentences (SD), and the duration of silence between words. Combining at least two feature categories achieved high accuracy in the schizophrenia classification. Prosodic and spectral or temporal features achieved the highest accuracy. The work with higher accuracy used the prosodic and spectral features QEVA, SDVV, and SSDL, which were derived from the F0 and spectrogram. The emotional state can be identified with most of the features previously mentioned (F0, I, F1, F2, F3, MFCCs, and SD), linear prediction cepstral coefficients (LPCC), linear spectral features (LSF), and the pause rate. Using the event-related potentials (ERP), the most promissory features found in the literature are mismatch negativity (MMN), P2, P3, P50, N1, and N2. The EEG features with higher accuracy in schizophrenia classification subjects are the nonlinear features, such as Cx, HFD, and Lya.

Prosodic Development During the Early School-Age Years

PURPOSE

This study used a cross-sequential design to identify developmental changes in narrative speech rhythm and intonation. The aim was to provide a robust, clinically relevant characterization of normative changes in speech prosody across the early school-age years.

METHOD

Structured spontaneous narratives were elicited annually from 60 children over a 3-year period. Children were aged 5-7 years at study outset and then were aged 7-9 years at study offset. Articulation rate, prominence spacing, and intonational phrase length and duration were calculated for each narrative to index speech rhythm; measures of pitch variability and pitch range indexed intonation. Linear mixed-effects (LME) models tested for cohort-based and within-subject longitudinal change on the prosodic measures; linear regression was used to test for the simple effect of age-in-months within year on the measures.

RESULTS

The LME analyses indicated systematic longitudinal changes in speech rhythm across all measures except phrase duration; there were no longitudinal changes in pitch variability or pitch range across the school-age years. Linear regression results showed an increase in articulation rate with age; there were no systematic differences between age cohorts across years in the study.

CONCLUSIONS

The results indicate that speech rhythm continues to develop during the school-age years. The results also underscore the very strong relationship between the rate and rhythm characteristics of speech and so suggest an important influence of speech motor skills on rhythm production. Finally, the results on pitch variability and pitch range are interpreted to suggest that these are inadequate measures of typical intonation development during the school-age years.

High Predictive Accuracy of Negative Schizotypy With Acoustic Measures

Negative schizotypal traits potentially can be digitally phenotyped using objective vocal analysis. Prior attempts have shown mixed success in this regard, potentially because acoustic analysis has relied on small, constrained feature sets. We employed machine learning to (a) optimize and cross-validate predictive models of self-reported negative schizotypy using a large acoustic feature set, (b) evaluate model performance as a function of sex and speaking task, (c) understand potential mechanisms underlying negative schizotypal traits by evaluating the key acoustic features within these models, and (d) examine model performance in its convergence with clinical symptoms and cognitive functioning. Accuracy was good (> 80%) and was improved by considering speaking task and sex. However, the features identified as most predictive of negative schizotypal traits were generally not considered critical to their conceptual definitions. Implications for validating and implementing digital phenotyping to understand and quantify negative schizotypy are discussed.

Speech Prosody as a Bridge Between Psychopathology and Linguistics: The Case of the Schizophrenia Spectrum

Patients with schizophrenia spectrum disorders experience severe difficulties in interpersonal communication, as described by traditional psychopathology and current research on social cognition. From a linguistic perspective, pragmatic abilities are crucial for successful communication. Empirical studies have shown that these abilities are significantly impaired in this group of patients. Prosody, the tone of voice with which words and sentences are pronounced, is one of the most important carriers of pragmatic meaning and can serve a range of functions from linguistic to emotional ones. Most of the existing literature on prosody of patients with schizophrenia spectrum disorders focuses on the expression of emotion, generally showing significant impairments. By contrast, the use of non-emotional prosody in these patients is scarcely investigated. In this paper, we first present a linguistic model to classify prosodic functions. Second, we discuss existing studies on the use of non-emotional prosody in these patients, providing an overview of the state of the art. Third, we delineate possible future lines of research in this field, also taking into account some classical psychopathological assumptions, for both diagnostic and therapeutic purposes.

Nonverbal Communication

The field of nonverbal communication (NVC) has a long history involving many cue modalities, including face, voice, body, touch, and interpersonal space; different levels of analysis, including normative, group, and individual differences; and many substantive themes that cross from psychology into other disciplines. In this review, we focus on NVC as it pertains to individuals and social interaction. We concentrate specifically on ( a) the meanings and correlates of cues that are enacted (sent) by encoders and ( b) the perception of nonverbal cues and the accuracy of such perception. Frameworks are presented for conceptualizing and understanding the process of sending and receiving nonverbal cues. Measurement issues are discussed, and theoretical issues and new developments are covered briefly. Although our review is primarily oriented within social and personality psychology, the interdisciplinary nature of NVC is evident in the growing body of research on NVC across many areas of scientific inquiry.

Right Hemisphere Regions Critical for Expression of Emotion Through Prosody

Impaired expression of emotion through pitch, loudness, rate, and rhythm of speech (affective prosody) is common and disabling after right hemisphere (RH) stroke. These deficits impede all social interactions. Previous studies have identified cortical areas associated with impairments of expression, recognition, or repetition of affective prosody, but have not identified critical white matter tracts. We hypothesized that: (1) differences across patients in specific acoustic features correlate with listener judgment of affective prosody and (2) these differences are associated with infarcts of specific RH gray and white matter regions. To test these hypotheses, 41 acute ischemic RH stroke patients had MRI diffusion weighted imaging and described a picture. Affective prosody of picture descriptions was rated by 21 healthy volunteers. We identified percent damage (lesion load) to each of seven regions of interest previously associated with expression of affective prosody and two control areas that have been associated with recognition but not expression of prosody. We identified acoustic features that correlated with listener ratings of prosody (hereafter “prosody acoustic measures”) with Spearman correlations and linear regression. We then identified demographic variables and brain regions where lesion load independently predicted the lowest quartile of each of the “prosody acoustic measures” using logistic regression. We found that listener ratings of prosody positively correlated with four acoustic measures. Furthermore, the lowest quartile of each of these four “prosody acoustic measures” was predicted by sex, age, lesion volume, and percent damage to the seven regions of interest. Lesion load in pars opercularis, supramarginal gyrus, or associated white matter tracts (and not control regions) predicted lowest quartile of the four “prosody acoustic measures” in logistic regression. Results indicate that listener perception of reduced affective prosody after RH stroke is due to reduction in specific acoustic features caused by infarct in right pars opercularis or supramarginal gyrus, or associated white matter tracts.

The assessment of nonverbal behavior in schizophrenia through the Formal Psychological Assessment

The nonverbal behavior (NVB) of people diagnosed with schizophrenia consistently interacts with their symptoms during the assessment. Previous studies frequently observed such an interaction when a prevalence of negative symptoms occurred. Nonetheless, a list of NVBs linked to negative symptoms needs to be defined. Furthermore, a list of items that can exhaustively assess such NVBs is still needed. The present study aims to introduce both lists by using the Formal Psychological Assessment. A deep analysis was performed on both the scientific literature and the DSM-5 for constructing the set of nonverbal behaviors; similarly, an initial list of 138 items investigating the behaviors was obtained from instruments used to assess schizophrenia. The Formal Psychological Assessment was then applied to reduce the preliminary list. A final list of 23 items necessary and sufficient to investigate the NVBs emerged. The list also allowed us to analyze specific relations among items. The present study shows how it is possible to deepen a patient's negative symptomatology, starting with the relations between items and the NVBs they investigate. Finally, this study examines the advantages and clinical implications of defining an assessment tool based on the found list of items.

Emotion processing deficits in the different dimensions of psychometric schizotypy

Schizotypy refers to a personality structure indicating "proneness" to schizophrenia. Around 10% of the general population has increased schizotypal traits, they also share other core features with schizophrenia and are thus at heightened risk for developing schizophrenia and spectrum disorders. A key aspect in schizophrenia-spectrum pathology is the impairment observed in emotion-related processes. This review summarizes findings on impairments related to central aspects of emotional processes, such as emotional disposition, alexithymia, facial affect recognition and speech prosody, in high schizotypal individuals in the general population. Although the studies in the field are not numerous, the current findings indicate that all these aspects of emotional processing are deficient in psychometric schizotypy, in accordance to the schizophrenia-spectrum literature. A disturbed frontotemporal neural network seems to be the critical link between these impairments, schizotypy and schizophrenia. The limitations of the current studies and suggestions for future research are discussed.

Can the Acoustic Analysis of Expressive Prosody Discriminate Schizophrenia?

Emotional states, attitudes and intentions are often conveyed by modulations in the tone of voice. Impaired recognition of emotions from a tone of voice (receptive prosody) has been described as characteristic symptoms of schizophrenia. However, the ability to express non-verbal information in speech (expressive prosody) has been understudied. This paper describes a useful technique for quantifying the degree of expressive prosody deficits in schizophrenia, using a semi-automatic method, and evaluates this method's ability to discriminate between patient and control groups. Forty-five medicated patients with a diagnosis of schizophrenia were matched with thirty-five healthy comparison subjects. Production of expressive prosodic speech was analyzed using variation in fundamental frequency (F0) measures on an emotionally neutral reading task. Results revealed that patients with schizophrenia exhibited significantly more pauses (p < .001), were slower (p < .001), and showed less pitch variability in speech (p < .05) and fewer variations in syllable timing (p < .001) than control subjects. These features have been associated with «flat» speech prosody. Signal processing algorithms applied to speech were shown to be capable of discriminating between patients and controls with an accuracy of 93.8%. These speech parameters may have a diagnostic and prognosis value and therefore could be used as a dependent measure in clinical trials.

Cognition and brain function in schizotypy: a selective review

Schizotypy refers to a set of personality traits thought to reflect the subclinical expression of the signs and symptoms of schizophrenia. Here, we review the cognitive and brain functional profile associated with high questionnaire scores in schizotypy. We discuss empirical evidence from the domains of perception, attention, memory, imagery and representation, language, and motor control. Perceptual deficits occur early and across various modalities. While the neural mechanisms underlying visual impairments may be linked to magnocellular dysfunction, further effects may be seen downstream in higher cognitive functions. Cognitive deficits are observed in inhibitory control, selective and sustained attention, incidental learning, and memory. In concordance with the cognitive nature of many of the aberrations of schizotypy, higher levels of schizotypy are associated with enhanced vividness and better performance on tasks of mental rotation. Language deficits seem most pronounced in higher-level processes. Finally, higher levels of schizotypy are associated with reduced performance on oculomotor tasks, resembling the impairments seen in schizophrenia. Some of these deficits are accompanied by reduced brain activation, akin to the pattern of hypoactivations in schizophrenia spectrum individuals. We conclude that schizotypy is a construct with apparent phenomenological overlap with schizophrenia and stable interindividual differences that covary with performance on a wide range of perceptual, cognitive, and motor tasks known to be impaired in schizophrenia. The importance of these findings lies not only in providing a fine-grained neurocognitive characterization of a personality constellation known to be associated with real-life impairments, but also in generating hypotheses concerning the aetiology of schizophrenia.

The normalities and abnormalities associated with speech in psychometrically-defined schizotypy

Speech deficits are thought to be an important feature of schizotypy--defined as the personality organization reflecting a putative liability for schizophrenia. There is reason to suspect that these deficits manifest as a function of limited cognitive resources. To evaluate this idea, we examined speech from individuals with psychometrically-defined schizotypy during a low cognitively-demanding task versus a relatively high cognitively-demanding task. A range of objective, computer-based measures of speech tapping speech production (silence, number and length of pauses, number and length of utterances), speech variability (global and local intonation and emphasis) and speech content (word fillers, idea density) were employed. Data for control (n=37) and schizotypy (n=39) groups were examined. Results did not confirm our hypotheses. While the cognitive-load task reduced speech expressivity for subjects as a group for most variables, the schizotypy group was not more pathological in speech characteristics compared to the control group. Interestingly, some aspects of speech in schizotypal versus control subjects were healthier under high cognitive load. Moreover, schizotypal subjects performed better, at a trend level, than controls on the cognitively demanding task. These findings hold important implications for our understanding of the neurocognitive architecture associated with the schizophrenia-spectrum. Of particular note concerns the apparent mismatch between self-reported schizotypal traits and objective performance, and the resiliency of speech under cognitive stress in persons with high levels of schizotypy.

Speech prosody abnormalities and specific dimensional schizotypy features: are relationships limited to male participants?

In schizophrenia, diminished vocal expressivity is associated with lower quality of life. Studies using computerized acoustic analysis of speech have found no evidence of diminished vocal prosody related to categorically defined schizotypy, a subclinical analogue of schizophrenia. However, existing studies have not examined the interaction between schizotypy and sex with vocal prosody measures. The current study examined 44 young adults (50% men) who were recruited to represent a continuous range of schizotypy. Speech samples were digitally recorded during autobiographical narratives and analyzed for prosody. In the male participants, variability of fundamental frequency and variability of intensity were each negatively related to the Schizotypal Personality Questionnaire (SPQ) ideas of reference subscale, whereas SPQ suspiciousness was related to a greater number of utterances, and SPQ odd behavior was related to a greater number of pauses. Because the relationships were restricted to men, and not significant in women, the results may explain earlier negative findings with schizotypy.

Automated computerized analysis of speech in psychiatric disorders

PURPOSE OF REVIEW

Disturbances in communication are a hallmark feature of severe mental illnesses. Recent technological advances have paved the way for objectifying communication using automated computerized semantic, linguistic and acoustic analyses. We review recent studies applying various computer-based assessments to the natural language produced by adult patients with severe mental illness.

RECENT FINDINGS

Automated computerized methods afford tools with which it is possible to objectively evaluate patients in a reliable, valid and efficient manner that complements human ratings. Crucially, these measures correlate with important clinical measures. The clinical relevance of these novel metrics has been demonstrated by showing their relationship to functional outcome measures, their in-vivo link to classic 'language' regions in the brain, and, in the case of linguistic analysis, their relationship to candidate genes for severe mental illness.

SUMMARY

Computer-based assessments of natural language afford a framework with which to measure communication disturbances in adults with severe mental illnesses. Emerging evidence suggests that they can be reliable and valid, and overcome many practical limitations of more traditional assessment methods. The advancement of these technologies offers unprecedented potential for measuring and understanding some of the most crippling symptoms of some of the most debilitating illnesses known to humankind.