Further evaluation of the binaural loudness ratio to predict speech intelligibility in vehicles and rooms
Résumé
This study compared the predictions of speech reception threshold (SRT) across conditions involving spatially distributed speech and noise in a vehicle and in a room, obtained with two prediction methods: the binaural speech-to-noise loudness ratio (BLR) metric proposed by Samardzic and Moore (2021) and the binaural speech intelligibility model (LAV) proposed by Lavandier et al. (2012) used here as a reference. Both methods provide SRT predictions with similar good accuracy for the vehicle experiments that involved background noise generated in a vehicle dynamometer test chamber and on road. The BLR model does not provide accurate SRT predictions for the room experiments that involved both single and multiple stationary noise sources simulated at different positions, for which the LAV model gives accurate predictions. Further analyses indicated that monaural information at the best ear is sufficient to describe the data well for the experiment with background noise generated in a vehicle dynamometer. They also revealed that such monaural analysis is not sufficient for accurate SRT predictions for the experiment with background noise generated on road, nor in the room conditions. Overall, the results indicated that the BLR method does not account for the better-ear listening and binaural unmasking effects underlying the corresponding variations in SRT, particularly in the room experiments.
Domaines
Acoustique [physics.class-ph]Origine | Fichiers produits par l'(les) auteur(s) |
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