An overview of the HASPI and HASQI metrics for predicting speech intelligibility and speech quality for normal hearing, hearing loss, and hearing aids.

Alterations of the speech signal, including additive noise and nonlinear distortion, can reduce speech intelligibility and quality. Hearing aids present an especially complicated situation since these devices may implement nonlinear processing designed to compensate for the hearing loss. Hearing-aid processing is often realized as time-varying multichannel gain adjustments, and may also include frequency reassignment. The challenge in designing metrics for hearing aids and hearing-impaired listeners is to accurately model the perceptual trade-offs between speech audibility and the nonlinear distortion introduced by hearing-aid processing. This paper focuses on the Hearing Aid Speech Perception Index (HASPI) and the Hearing Aid Speech Quality Index (HASQI) as representative metrics for predicting intelligibility and quality. These indices start with a model of the auditory periphery that can be adjusted to represent hearing loss. The peripheral model, the speech features computed from the model outputs, and the procedures used to fit the features to subject data are described. Examples are then presented for using the metrics to measure the effects of additive noise, evaluate noise-suppression processing, and to measure the differences among commercial hearing aids. Open questions and considerations in using these and related metrics are then discussed.