title: Evaluation of Voice Acoustics as Predictors of Clinical Depression Scores.
abstract: OBJECTIVE
  The aim of the present study was to determine if acoustic measures of voice, characterizing specific spectral and timing properties, predict clinical ratings of depression severity measured in a sample of patients using the Hamilton Depression Rating Scale (HAMD) and Beck Depression Inventory (BDI-II).
  
  
  METHODS
  This is a prospective study.
  
  
  METHODS
  Voice samples and clinical depression scores were collected prospectively from consenting adult patients who were referred to psychiatry from the adult emergency department or primary care clinics. The patients were audio-recorded as they read a standardized passage in a nearly closed-room environment. Mean Absolute Error (MAE) between actual and predicted depression scores was used as the primary outcome measure.
  
  
  RESULTS
  The average MAE between predicted and actual HAMD scores was approximately two scores for both men and women, and the MAE for the BDI-II scores was approximately one score for men and eight scores for women. Timing features were predictive of HAMD scores in female patients while a combination of timing features and spectral features was predictive of scores in male patients. Timing features were predictive of BDI-II scores in male patients.
  
  
  CONCLUSIONS
  Voice acoustic features extracted from read speech demonstrated variable effectiveness in predicting clinical depression scores in men and women. Voice features were highly predictive of HAMD scores in men and women, and BDI-II scores in men, respectively. The methodology is feasible for diagnostic applications in diverse clinical settings as it can be implemented during a standard clinical interview in a normal closed room and without strict control on the recording environment.
authors.affiliation: Department of Electrical Engineering, Vanderbilt University, Nashville, Tennessee.
authors.forename: Nik Wahidah
authors.initials: NW
authors.lastname: Hashim
authors.affiliation: Department of Electrical Engineering, Vanderbilt University, Nashville, Tennessee.
authors.forename: Mitch
authors.initials: M
authors.lastname: Wilkes
authors.affiliation: Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee.
authors.forename: Ronald
authors.initials: R
authors.lastname: Salomon
authors.affiliation: Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee.
authors.forename: Jared
authors.initials: J
authors.lastname: Meggs
authors.affiliation: Department of Anesthesiology, Vanderbilt University School of Medicine, Nashville, Tennessee. Electronic address: Dan.france@vanderbilt.edu.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: France
mesh_terms: D000162:Acoustics; D000328:Adult; D000339:Affect; D003863:Depression / Q000175:diagnosis* / Q000503:physiopathology / Q000523:psychology; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011569:Psychiatric Status Rating Scales; D012720:Severity of Illness Index; D013018:Sound Spectrography; D013061:Speech Acoustics; D013068:Speech Production Measurement; D059020:Suicidal Ideation; D013997:Time Factors; D014833:Voice Quality
keywords: acoustics; depression; prediction; severity; voice