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Article
Objective quality and intelligibility prediction for users of assistive listening devices: Advantages and limitations of existing tools
IEEE Signal Processing Magazine
  • Tiago H. Falk, University of Toronto
  • Vijay Parsa, The University of Western Ontario
  • Joao F. Santos, Universidade Federal de Santa Catarina
  • Kathryn Arehart, University of Colorado Boulder
  • Oldooz Hazrati, The University of Texas at Dallas
  • Rainer Huber, National Center of Competence for Hearing Aid System Technology
  • James M. Kates, University of Colorado Boulder
  • Susan Scollie, The University of Western Ontario
Document Type
Article
Publication Date
3-1-2015
URL with Digital Object Identifier
10.1109/MSP.2014.2358871
Abstract

This article presents an overview of 12 existing objective speech quality and intelligibility prediction tools. Two classes of algorithms are presented?intrusive and nonintrusive?with the former requiring the use of a reference signal, while the latter does not. Investigated metrics include both those developed for normal hearing (NH) listeners, as well as those tailored particularly for hearing impaired (HI) listeners who are users of assistive listening devices [i.e., hearing aids (HAs) and cochlear implants (CIs)]. Representative examples of those optimized for HI listeners include the speech-to-reverberation modulation energy ratio (SRMR), tailored to HAs (SRMR-HA) and to CIs (SRMR-CI); the modulation spectrum area (ModA); the HA speech quality (HASQI) and perception indices (HASPI); and the perception-model-based quality prediction method for hearing impairments (PEMO-Q-HI). The objective metrics are tested on three subjectively rated speech data sets covering reverberation-alone, noise-alone, and reverberation-plus-noise degradation conditions, as well as degradations resultant from nonlinear frequency compression and different speech enhancement strategies. The advantages and limitations of each measure are highlighted and recommendations are given for suggested uses of the different tools under specific environmental and processing conditions.

Citation Information
Tiago H. Falk, Vijay Parsa, Joao F. Santos, Kathryn Arehart, et al.. "Objective quality and intelligibility prediction for users of assistive listening devices: Advantages and limitations of existing tools" IEEE Signal Processing Magazine Vol. 32 Iss. 2 (2015) p. 114 - 124
Available at: http://works.bepress.com/susan-scollie/32/