Prosodic analysis of speech and the underlying mental state

Roi Kliper, Shirley Portuguese, Daphna Weinshall*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations


Speech is a measurable behavior that can be used as a biomarker for various mental states including schizophrenia and depression. In this paper we show that simple temporal domain features, extracted from conversational speech, may highlight alterations in acoustic characteristics that are manifested in changes in speech prosody - these changes may, in turn, indicate an underlying mental condition. We have developed automatic computational tools for the monitoring of pathological mental states - including characterization, detection, and classification. We show that some features strongly correlate with perceptual diagnostic evaluation scales of both schizophrenia and depression, suggesting the contribution of such acoustic speech properties to the perception of an apparent mental condition. We further show that one can use these temporal domain features to correctly classify up to 87.5% and up to 70% of the speakers in a two-way and in a three-way classification tasks respectively.

Original languageAmerican English
Title of host publicationPervasive Computing Paradigms for Mental Health - 5th International Conference, MindCare 2015, Revised Selected Papers
EditorsDimitris Giakoumis, Guillaume Lopez, Aleksandar Matic, Silvia Serino, Pietro Cipresso
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783319322698
StatePublished - 2016
Event5th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2015 - Milan, Italy
Duration: 24 Sep 201525 Sep 2015

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929


Conference5th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2015

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2016.


  • Jitter
  • Machine learning
  • Mental health
  • Schizophrenia
  • Shimmer
  • Speech prosody


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