For the Clarity Workshop in 2021, James Kates gave a talk on hearing-aid processed speech. This talk and the rest of the workshop are freely available online.
Signal degradations, such as additive noise and nonlinear distortion, can reduce the intelligibility and quality of a speech signal. Predicting intelligibility and quality for hearing aids is especially difficult since these devices may contain intentional nonlinear distortion designed to make speech more audible to a hearing-impaired listener. This speech processing often takes the form of time-varying multichannel gain adjustments. Intelligibility and quality metrics used for hearing aids and hearing-impaired listeners must therefore consider the trade-offs between audibility and distortion introduced by hearing-aid speech envelope modifications. This presentation uses the Hearing Aid Speech Perception Index (HASPI) and the Hearing Aid Speech Quality Index (HASQI) to predict intelligibility and quality, respectively. These indices incorporate a model of the auditory periphery that can be adjusted to reflect hearing loss. They have been trained on intelligibility scores and quality ratings from both normal-hearing and hearing-impaired listeners for a wide variety of signal and processing conditions. The basics of the metrics are explained, and the metrics are then used to analyze the effects of additive noise on speech, to evaluate noise suppression algorithms, and to measure differences among commercial hearing aids.