Major depressive disorder discrimination using vocal acoustic features

• Published in: Journal of affective disorders Vol. 225; pp. 214 - 220
• Main Authors: Taguchi, Takaya, Tachikawa, Hirokazu, Nemoto, Kiyotaka, Suzuki, Masayuki, Nagano, Toru, Tachibana, Ryuki, Nishimura, Masafumi, Arai, Tetsuaki
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.01.2018
• Subjects: Acoustic features; Adult; Aged; Biomarker; Depression; Depressive Disorder, Major - diagnosis; Discriminant Analysis; Female; Humans; Male; MFCC; Middle Aged; Psychiatric/Mental Health; Speech Acoustics; Voice analysis; Voice Disorders - diagnosis; Young Adult; Depression; Biomarker; Discriminant analysis; Voice analysis; MFCC; Acoustic features
• ISSN: 0165-0327; 1573-2517; 1573-2517
• DOI: 10.1016/j.jad.2017.08.038

The voice carries various information produced by vibrations of the vocal cords and the vocal tract. Though many studies have reported a relationship between vocal acoustic features and depression, including mel-frequency cepstrum coefficients (MFCCs) which applied to speech recognition, there have been few studies in which acoustic features allowed discrimination of patients with depressive disorder. Vocal acoustic features as biomarker of depression could make differential diagnosis of patients with depressive state. In order to achieve differential diagnosis of depression, in this preliminary study, we examined whether vocal acoustic features could allow discrimination between depressive patients and healthy controls. Subjects were 36 patients who met the criteria for major depressive disorder and 36 healthy controls with no current or past psychiatric disorders. Voices of reading out digits before and after verbal fluency task were recorded. Voices were analyzed using OpenSMILE. The extracted acoustic features, including MFCCs, were used for group comparison and discriminant analysis between patients and controls. The second dimension of MFCC (MFCC 2) was significantly different between groups and allowed the discrimination between patients and controls with a sensitivity of 77.8% and a specificity of 86.1%. The difference in MFCC 2 between the two groups reflected an energy difference of frequency around 2000–3000Hz. The MFCC 2 was significantly different between depressive patients and controls. This feature could be a useful biomarker to detect major depressive disorder. Sample size was relatively small. Psychotropics could have a confounding effect on voice. •Vocal acoustic features of patients with depression and controls were analyzed.•Mel-frequency cepstrum coefficient 2 (MFCC2) was different between groups.•MFCC2 discriminated patients with depression and controls with 81.9% accuracy.•MFCC2 might reflect change of the quality of voice in depressive disorder patients.