English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This study investigates the speech articulatory coordination in schizophreniasubjects exhibiting strong positive symptoms (e.g.hallucinations anddelusions), using a time delay embedded correlation analysis. We show that theschizophrenia subjects with strong positive symptoms and who are markedly illpose complex coordination patterns in facial and speech gestures than what isobserved in healthy subjects. This observation is in contrast to what previousstudies have shown in Major Depressive Disorder (MDD), where subjects with MDDshow a simpler coordination pattern with respect to healthy controls orsubjects in remission. This difference is not surprising given MDD isnecessarily accompanied by Psychomotor slowing (i.e.,negative symptoms) whichaffects speech, ideation and motility. With respect to speech, psychomotorslowing results in slowed speech with more and longer pauses than what occursin speech from the same speaker when they are in remission and from a healthysubject. Time delay embedded correlation analysis has been used to quantify thedifferences in coordination patterns of speech articulation. The current studyis based on 17 Facial Action Units (FAUs) extracted from video data and 6 VocalTract Variables (TVs) obtained from simultaneously recorded audio data. The TVsare extracted using a speech inversion system based on articulatory phonologythat maps the acoustic signal to vocal tract variables. The high-level timedelay embedded correlation features computed from TVs and FAUs are used totrain a stacking ensemble classifier fusing audio and video modalities. Theresults show that there is a promising distinction between healthy andschizophrenia subjects (with strong positive symptoms) in terms of neuromotorcoordination in speech.

Inverted Vocal Tract Variables and Facial Action Units to Quantify Neuromotor Coordination in Schizophrenia