OPRA-RS: A Hearing-Aid Fitting Method Based on Automatic Speech Recognition and Random Search

Autor: Libio Gonçalves Braz, Lionel Fontan, Julien Pinquier, Michael A. Stone, Christian Füllgrabe

Publikováno v: Frontiers in Neuroscience, Vol 16 (2022)

Hearing-aid (HA) prescription rules (such as NAL-NL2, DSL-v5, and CAM2) are used by HA audiologists to define initial HA settings (e.g., insertion gains, IGs) for patients. This initial fitting is later individually adjusted for each patient to impro

Externí odkaz: https://doaj.org/article/acbe6b60200142d882680d7b5d749f90

Apport du geste dans l'acquisition de la prononciation en L2 : quand la réalité ne correspond pas aux attentes

Autor: Charlotte Alazard, Leonardo Contreras Roa, Marie Philippart de Foy, Lionel Fontan, Nadia Yassine-Diab, Julien Pinquier, Isabelle Ferrané

Publikováno v: XXXIVe Journées d'Études sur la Parole -- JEP 2022.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b3d53e42754013819e60ac2c15cdacdb
https://doi.org/10.21437/jep.2022-77

Computer-assisted assessment of phonetic fluency in a second language: a longitudinal study of Japanese learners of French

Autor: Maxime Le Coz, Sylvain Detey, Lionel Fontan, Saïd Jmel

Publikováno v: Speech Communication. 125:69-79

Automatic second language (L2) speech fluency assessment has been one of the ultimate goals of several projects aiming at designing Computer-Assisted Pronunciation Training (CAPT) tools for L2 learners. Usually, three challenges must be tackled in or

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7ca8934bae834376b468e4fb769a0f4d
https://doi.org/10.1016/j.specom.2020.10.001

Using Automatic Speech Recognition to Optimize Hearing-Aid Time Constants

Autor: Lionel, Fontan, Libio, Gonçalves Braz, Julien, Pinquier, Michael A, Stone, Christian, Füllgrabe

Publikováno v: Frontiers in neuroscience. 16

Automatic speech recognition (ASR), when combined with hearing-aid (HA) and hearing-loss (HL) simulations, can predict aided speech-identification performances of persons with age-related hearing loss. ASR can thus be used to evaluate different HA co

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::823208840876501745946b8519e0bdd0
https://pubmed.ncbi.nlm.nih.gov/35368250

Improving hearing-aid gains based on automatic speech recognition

Autor: Michael A. Stone, Maxime Le Coz, Lionel Fontan, Christian Füllgrabe, Charlotte Azzopardi

Publikováno v: Fontan, L, Le Coz, M, Azzopardi, C, Stone, M & Füllgrabe, C 2020, ' Improving hearing-aid gains based on automatic speech recognition ', The Journal of the Acoustical Society of America, vol. 148, no. 3, pp. EL227-EL233 . https://doi.org/10.1121/10.0001866

This study provides proof of concept that automatic speech recognition (ASR)can be used to improve hearing aid (HA) fitting. A signal-processing chain consisting of a HA simulator, a hearing-loss simulator, and an ASR system normalizing the intensity

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8ed7362099f39db10d45577f2664f87
https://www.research.manchester.ac.uk/portal/en/publications/improving-hearingaid-gains-based-on-automatic-speech-recognition(d6449296-418f-416f-8b29-5ad4b4f960d4).html