Speech Intelligibility for Target and Masker with Different Spectra

Abstract

The speech intelligibility index (SII) calculation is based on the assumption that the effective range of signal-to-noise ratio (SNR) regarding speech intelligibility is [− 15 dB; +15 dB]. In a specific frequency band, speech intelligibility would remain constant by varying the SNRs above + 15 dB or below − 15 dB. These assumptions were tested in four experiments measuring speech reception thresholds (SRTs) with a speech target and speech-spectrum noise, while attenuating target or noise above or below 1400 Hz, with different levels of attenuation in order to test different SNRs in the two bands. SRT varied linearly with attenuation at low-attenuation levels and an asymptote was reached for high-attenuation levels. However, this asymptote was reached (intelligibility was not influenced by further attenuation) for different attenuation levels across experiments. The − 15-dB SII limit was confirmed for highpass filtered targets, whereas for low-pass filtered targets, intelligibility was further impaired by decreasing the SNR below − 15 dB (until − 37 dB) in the high-frequency band. For high-pass and low-pass filtered noises, speech intelligibility kept improving when increasing the SNR in the rejected band beyond + 15 dB (up to 43 dB). Before reaching the asymptote, a 10-dB increase of SNR obtained by filtering the noise resulted in a larger decrease of SRT than a corresponding 10-dB decrease of SNR obtained by filtering the target (the slopes SRT/attenuation were different depending on which source was filtered). These results question the use of the SNR range and the importance function adopted by the SII when considering sharply filtered signals.Keywords Speech intelligibility index · Speech in noise · Speech intelligibility measurement 258 T. Leclère et al.

A series of SNR-based speech intelligibility models in the Auditory Modeling Toolbox

“…Even if the models can predict the influence of having target and maskers with different spectra, providing that the impulse responses are filtered accordingly for jelfs2011, only broadband stimuli should be considered. In our experience and as in other modelling approaches, predictions fail for sharply filtered stimuli [15,24]. 2012) [20] with a stationary speechspectrum noise (SSN) simulated at two distances (near, far) in three directions (left, front, right) in a meeting room, using BRIRs (blue; binaural unmasking and better-ear listening involved) and SEIRs (red; no binaural unmasking).…”