Communication Dans Un Congrès Année : 2021

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.

Fichier principal
Vignette du fichier
000623.pdf (407.48 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence
DOI

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

DOI

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

Dates et versions

hal-03345050 , version 1 (15-09-2021)

Licence

Identifiants

  • HAL Id : hal-03345050 , version 1

Citer

Alejandro Osses, Léo Varnet. Consonant-in-noise discrimination using an auditory model with different speech-based decision devices. DAGA, Aug 2021, Vienne, Austria. pp.298-301. ⟨hal-03345050⟩
242 Consultations
248 Téléchargements

Partager

  • More