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EURASIP Journal on Advances in Signal Processing

, 2011:42

Emotion and Mental State Recognition from Speech

Abstract

Of increasing importance in the civilian and military population is the recognition of major depressive disorder at its earliest stages and intervention before the onset of severe symptoms. Toward the goal of more effective monitoring of depression severity, we introduce vocal biomarkers that are derived automatically from phonologically-based measures of speech rate. To assess our measures, we use a 35-speaker free-response speech database of subjects treated for depression over a 6-week duration. We find that dissecting average measures of speech rate into phone-specific characteristics and, in particular, combined phone-duration measures uncovers stronger relationships between speech rate and depression severity than global measures previously reported for a speech-rate biomarker. Results of this study are supported by correlation of our measures with depression severity and classification of depression state with these vocal measures. Our approach provides a general framework for analyzing individual symptom categories through phonological units, and supports the premise that speaking rate can be an indicator of psychomotor retardation severity.

Keywordsmajor depressive disorder vocal biomarkers speech rate speech phone clinical HAMD AbbreviationsDALYsdisability-adjusted life years

MDDmajor depressive disorder

MDEmajor depressive episodes

RMSEroot mean squared error

SVMsupport vector machine

YLDyears lost due to disability.

Electronic supplementary materialThe online version of this article doi:10.1186-1687-6180-2011-42 contains supplementary material, which is available to authorized users.

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Author: Andrea Carolina Trevino - Thomas Francis Quatieri - Nicolas Malyska

Source: https://link.springer.com/



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