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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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Major depressive disorder discrimination using vocal acoustic features.

Takaya Taguchi1, Hirokazu Tachikawa2, Kiyotaka Nemoto2

  • 1Department of Psychiatry, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Japan; University of Tsukuba Hospital, Japan.

Journal of Affective Disorders
|August 26, 2017
PubMed
Summary

Vocal acoustic features, specifically Mel-frequency cepstrum coefficients 2 (MFCC 2), can help distinguish individuals with major depressive disorder from healthy controls. This finding suggests MFCC 2 may serve as a potential biomarker for depression detection.

Keywords:
Acoustic featuresBiomarkerDepressionDiscriminant analysisMFCCVoice analysis

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Area of Science:

  • Psychiatry
  • Speech Science
  • Biomedical Engineering

Background:

  • Vocal acoustic features offer insights into physiological and psychological states.
  • While links between voice characteristics and depression exist, few studies have used acoustic features for direct patient discrimination.
  • Developing vocal biomarkers for depression could aid in differential diagnosis.

Purpose of the Study:

  • To investigate if vocal acoustic features can discriminate between patients with major depressive disorder and healthy individuals.
  • To explore the potential of acoustic voice analysis as a diagnostic tool for depression.

Main Methods:

  • 36 patients with major depressive disorder and 36 healthy controls participated.
  • Voice recordings were analyzed using OpenSMILE software.
  • Extracted acoustic features, including Mel-frequency cepstrum coefficients (MFCCs), were used for discriminant analysis.

Main Results:

  • The second dimension of MFCC (MFCC 2) showed significant differences between depressive patients and controls.
  • MFCC 2 achieved 77.8% sensitivity and 86.1% specificity in discriminating between the groups.
  • The observed difference in MFCC 2 relates to energy variations in the 2000-3000Hz frequency range.

Conclusions:

  • MFCC 2 is a significant acoustic feature differentiating individuals with depression from controls.
  • This vocal biomarker shows promise for the detection of major depressive disorder.