Prediction of speech intelligibility in spatial noise and reverberation for normal-hearing and hearing-impaired listeners

Abstract

Binaural speech intelligibility of individual listeners under realistic conditions was predicted using a model consisting of a gammatone filter bank, an independent equalization-cancellation (EC) process in each frequency band, a gammatone resynthesis, and the speech intelligibility index (SII). Hearing loss was simulated by adding uncorrelated masking noises (according to the pure-tone audiogram) to the ear channels. Speech intelligibility measurements were carried out with 8 normal-hearing and 15 hearing-impaired listeners, collecting speech reception threshold (SRT) data for three different room acoustic conditions (anechoic, office room, cafeteria hall) and eight directions of a single noise source (speech in front). Artificial EC processing errors derived from binaural masking level difference data using pure tones were incorporated into the model. Except for an adjustment of the SII-to-intelligibility mapping function, no model parameter was fitted to the SRT data of this study. The overall correlation coefficient between predicted and observed SRTs was 0.95. The dependence of the SRT of an individual listener on the noise direction and on room acoustics was predicted with a median correlation coefficient of 0.91. The effect of individual hearing impairment was predicted with a median correlation coefficient of 0.95. However, for mild hearing losses the release from masking was overestimated.

Binaural Glimpses at the Cocktail Party?

“…described by the classic equalization-cancellation (EC) model (Durlach 1963). This model can account for binaural unmasking in psychoacoustics and was successfully combined with a speech intelligibility model (eSII; Rhebergen et al 2006) in the (short-time) binaural speech intelligibility model (BSIM; Beutelmann and Brand 2006;Beutelmann et al 2010). A conceptually similar approach was suggested by Lavandier and Culling (2010).…”

Objective perceptual quality assessment for self-steering binaural hearing aid microphone arrays

“…Binaural SRT / ΔSRT: The speech reception threshold (SRT) is defined as the signal-to-noise ratio (SNR) at 50% speech intelligibility. In [10] a binaural model of speech intelligibility based on the equalization-cancelation (EC) processing by Durlach had been defined which is able to predict the SRT with high accuracy. If the estimated SRT for the output of a noise reduction scheme is lower than for the input signal this means that the speech intelligibility has increased due to the algorithm.…”

“…However, as the speech intelligibility is a nonlinear function of the SNR and other signal features such as the preservation of binaural cues, we use the difference between output and input SRT, namely the ΔSRT, as an indirect measure for the increase of intelligibility. The binaural SRT measure as described in [10,1] assumes a spatially stationary source configuration. To be applicable to moving sources it had to be extended to a block-wise measure with subsequent averaging across blocks.…”

Improving the conditioning of the optimization criterion in acoustic multi-channel equalization using shorter reshaping filters

“…While early reverberation may be desirable [1][2][3], late reverberation may degrade the perceived speech quality and intelligibility [4][5][6] as well as the performance of automatic speech recognition systems [7,8]. In order to mitigate these detrimental effects of reverberation, several single-channel and A well-known complete multi-channel equalization technique aiming at acoustic system inversion is the multiple-input/output inverse theorem (MINT)-based technique [19], which however suffers from drawbacks in practice.…”