The Hearing-Aid Speech Perception Index (HASPI) Version 2.

• We propose a revised intelligibility index based on the outputs of an auditory model. • The auditory model incorporates peripheral hearing loss and is accurate for both normal and impaired hearing. • The index compares the model outputs for a processed signal with the outputs for an unprocessed reference signal. • The index uses measurements of envelope fidelity calculated using a modulation filterbank • Index results are presented for noise, distortion, reverberation, and nonlinear signal processing outputs. This paper presents a revised version of the Hearing-Aid Speech Perception Index (HASPI). The index is based on a model of the auditory periphery that incorporates changes due to hearing loss and is valid for both normal-hearing and hearing-impaired listeners. It is an intrusive metric that compares the time-frequency envelope and temporal fine structure (TFS) of a degraded signal to an unprocessed reference. The first modification to HASPI is an extension to the range of envelope modulation rates considered in the metric. HASPI applies a lowpass filter to the time-frequency envelope modulation, and in the new version this single filter is replaced by a modulation filterbank. The temporal fine structure (TFS) analysis in the original version of HASPI is replaced by the filterbank outputs at higher modulation rates that represent auditory roughness and periodicity. The second modification is replacing the parametric model combining envelope and TFS measurements used in the original version with an ensemble of neural networks. The improved version of HASPI is compared to the original version for datasets from five experiments that encompass noise and nonlinear distortion, frequency compression, ideal binary mask noise suppression, speech modified using a noise vocoder, and speech in reverberation. The new version of HASPI is shown to have a statistically-significant reduction in RMS error compared to the original version for most of the data considered, and to be significantly more accurate for speech in reverberation. [ABSTRACT FROM AUTHOR]