Ecologically valid long-term mood monitoring of individuals with bipolar disorder using speech

Zahi N. Karam, Emily Mower Provost, Satinder Singh, Jennifer Montgomery, Christopher Archer, Gloria Harrington, Melvin G. McInnis

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Speech patterns are modulated by the emotional and neurophysiological state of the speaker. There exists a growing body of work that computationally examines this modulation in patients suffering from depression, autism, and post-traumatic stress disorder. However, the majority of the work in this area focuses on the analysis of structured speech collected in controlled environments. Here we expand on the existing literature by examining bipolar disorder (BP). BP is characterized by mood transitions, varying from a healthy euthymic state to states characterized by mania or depression. The speech patterns associated with these mood states provide a unique opportunity to study the modulations characteristic of mood variation. We describe methodology to collect unstructured speech continuously and unobtrusively via the recording of day-to-day cellular phone conversations. Our pilot investigation suggests that manic and depressive mood states can be recognized from this speech data, providing new insight into the feasibility of unobtrusive, unstructured, and continuous speech-based wellness monitoring for individuals with BP.

    Original languageEnglish (US)
    Title of host publication2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages4858-4862
    Number of pages5
    ISBN (Print)9781479928927
    DOIs
    StatePublished - 2014
    Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
    Duration: May 4 2014May 9 2014

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    ISSN (Print)1520-6149

    Other

    Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
    CountryItaly
    CityFlorence
    Period5/4/145/9/14

    Keywords

    • Bipolar Disorder
    • Speech Analysis
    • mood modeling

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Electrical and Electronic Engineering

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