Takaya Taguchi1, Hirokazu Tachikawa2, Kiyotaka Nemoto3, Masayuki Suzuki4, Toru Nagano4, Ryuki Tachibana4, Masafumi Nishimura5, Tetsuaki Arai3. 1. Department of Psychiatry, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Japan; University of Tsukuba Hospital, Japan. 2. Department of Psychiatry, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Japan; Department of Psychiatry, Faculty of Medicine, University of Tsukuba, Japan. Electronic address: tachikawa@md.tsukuba.ac.jp. 3. Department of Psychiatry, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Japan; Department of Psychiatry, Faculty of Medicine, University of Tsukuba, Japan. 4. IBM Japan, LTD., IBM Research, Tokyo, Japan. 5. Graduate School of Integrated Science and Technology, Shizuoka University, Japan.
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: The MFCC 2 was significantly different between depressive patients and controls. This feature could be a useful biomarker to detect major depressive disorder. LIMITATIONS: Sample size was relatively small. Psychotropics could have a confounding effect on voice.
BACKGROUND: 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 depressivepatients and healthy controls. METHODS: 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. RESULTS: 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. CONCLUSIONS: The MFCC 2 was significantly different between depressivepatients and controls. This feature could be a useful biomarker to detect major depressive disorder. LIMITATIONS: Sample size was relatively small. Psychotropics could have a confounding effect on voice.
Authors: Bethany Little; Ossama Alshabrawy; Daniel Stow; I Nicol Ferrier; Roisin McNaney; Daniel G Jackson; Karim Ladha; Cassim Ladha; Thomas Ploetz; Jaume Bacardit; Patrick Olivier; Peter Gallagher; John T O'Brien Journal: Psychol Med Date: 2020-01-16 Impact factor: 7.723