Consonant-in-noise discrimination using an auditory model with different speech-based decision devices
Résumé
This study presents insights into the discrimination of two consonants presented in vowel-consonant-vowel (VCV) words embedded in speech-shaped noise (SSN) by adopting an auditory model that uses a modulation filter bank front-end followed by either of two speech back-end decision modules from the literature. These decision modules have been validated in the past for the discrimination of sentences in closed-and open-sets. Our analysis is focused on the discrimination cues available to the model, evaluating whether these cues might be further used to simulate listener-dependent performance. For that purpose we will rely on a reverse correlation approach by comparing the noise representations that lead to the choice of one or the other consonant.
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Cite 10.5281/zenodo.5483835 Jeu de données Osses, A., & Varnet, L. (2021). Noise data for the study of consonant-in-noise discrimination using an auditory model with different speech-based decision devices [Data set]. Zenodo. https://doi.org/10.5281/ZENODO.5483835
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Cite 10.5281/zenodo.5500139 Ouvrage Uglyrocks & LeoVarnet. (2021). aosses-tue/fastACI: fastACI v1.0 (Version v1.0). Zenodo. https://doi.org/10.5281/ZENODO.5500139