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Digital Object Identifier 10.1109/MSP.2014.2358871

Date of publication: 12 February 2015

his article presents an overview of 12 existing

objective speech quality and intelligibility predic-

tion tools. Two classes of algorithms are pre-

sented—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-rever-

beration 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 pre-

diction 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 rever-

beration-plus-noise degradation conditions, as well as degrada-

tions resultant from nonlinear frequency compression and

different speech enhancement strategies. The advantages and

limitations of each measure are highlighted and recommenda-

tions are given for suggested uses of the different tools under

specific environmental and processing conditions.

INTRODUCTION

According to 2005 estimates from the World Health Organization,

278 million people worldwide had moderate to profound hearing

loss in one or both ears. Depending on the degree of hearing

[

Tiago H. Falk, Vijay Parsa, João F. Santos, Kathryn Arehart, Oldooz Hazrati,

Rainer Huber, James M. Kates, and Susan Scollie

]

[

Advantages and limitations of existing tools

]

Objective Quality

and Intelligibility

Prediction for Users of

Assistive Listening Devices

EARPHONES—IMAGE LICENSED BY INGRAM PUBLISHING

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