title: Speech intelligibility estimation using multi-resolution spectral features for speakers undergoing cancer treatment.
abstract: Head and neck cancer can significantly hamper speech production which often reduces speech intelligibility. A method of extracting spectral features is presented. The method uses a multi-resolution sinusoidal transform scheme, which enables better representation of spectral and harmonic characteristics. Regression methods were used to predict interval-scaled intelligibility scores of utterances in the NKI-CCRT speech corpus. The inclusion of these features lowered the mean squared estimation error from 0.43 to 0.39 on a scale from 1 to 7, with a p-value less than 0.001. For binary intelligibility classification, their inclusion resulted in an improvement by 5.0 percentage points when tested on a disjoint set.
authors.affiliation: School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 jon.kim@gatech.edu, hrishikesh@gatech.edu, clements@gatech.edu.
authors.forename: Jonathan C
authors.initials: JC
authors.lastname: Kim
authors.affiliation: School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 jon.kim@gatech.edu, hrishikesh@gatech.edu, clements@gatech.edu.
authors.forename: Hrishikesh
authors.initials: H
authors.lastname: Rao
authors.affiliation: School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 jon.kim@gatech.edu, hrishikesh@gatech.edu, clements@gatech.edu.
authors.forename: Mark A
authors.initials: MA
authors.lastname: Clements
mesh_terms: D000162:Acoustics; D059248:Chemoradiotherapy / Q000009:adverse effects; D006258:Head and Neck Neoplasms / Q000150:complications / Q000628:therapy*; D006801:Humans; D016018:Least-Squares Analysis; D025341:Principal Component Analysis; D012044:Regression Analysis; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D013061:Speech Acoustics; D013065:Speech Intelligibility; D013068:Speech Production Measurement / Q000379:methods*; D014833:Voice Quality