LAVANDIER Mathieu

Developing a new tool to improve speech processing and spatial perception in noisy environments by hearing aids

Project status: closed

In our aging population, hearing problems are becoming increasingly common. In a noisy environment, being able to spatially separate a voice from surrounding noise can greatly improve our understanding of speech. People with healthy hearing have this ability, unlike people with hearing loss, including those equipped with hearing aids.

It is essential to make the appropriate hearing aids available to people with hearing loss to enable them to participate actively in society. The aim of Dr. Lavandier’s research project is to facilitate new therapeutic strategies for hearing aids, which could restore the spatial properties of speech.

To this end, he will develop a model for predicting speech comprehension, taking into account individual hearing loss and the help brought by hearing aids in noisy and complex but real environments such as sound reverberation or the simultaneous presence of voices.

This work will enable improvements in hearing aids, while also being very useful for improving building comfort and accessibility, which currently rely on standards for people with normal hearing.

Doctor Mathieu Lavandier
Investigator
National School of State Public Works (Ecole Nationale des Travaux Publics de l’Etat, ENTPE), Vaulx-en-Velin, France

Related scientific publication(s) :

Virginia Best, Elin Roverud , Lucas Baltzell, Jan Rennies, Mathieu Lavandier. The importance of a broad bandwidth for understanding "glimpsed" speech. J Acoust Soc Am. 2019 Nov;146(5):3215. doi: 10.1121/1.5131651.
Thibault Vicente, Mathieu Lavandier. Further validation of a binaural model predicting speech intelligibility against envelope-modulated noises. Hear Res. 2020 May;390:107937. doi: 10.1016/j.heares.2020.107937. Epub 2020 Mar 6.
Lucas S Baltzell, Jayaganesh Swaminathan, Adrian Y Cho, Mathieu Lavandier, Virginia Best. Binaural sensitivity and release from speech-on-speech masking in listeners with and without hearing loss. J Acoust Soc Am. 2020 Mar;147(3):1546. doi: 10.1121/10.0000812.
Thibault Vicente, Mathieu Lavandier, Jörg M Buchholz. A binaural model implementing an internal noise to predict the effect of hearing impairment on speech intelligibility in non-stationary noises. J Acoust Soc Am. 2020 Nov;148(5):3305. doi: 10.1121/10.0002660.
Luna Prud'homme, Mathieu Lavandier, Virginia Best. A harmonic-cancellation-based model to predict speech intelligibility against a harmonic masker. J Acoust Soc Am. 2020 Nov;148(5):3246. doi: 10.1121/10.0002492.
Peter A Wasiuk, Mathieu Lavandier, Emily Buss, Jacob Oleson, Lauren Calandruccio. The effect of fundamental frequency contour similarity on multi-talker listening in older and younger adults. J Acoust Soc Am. 2020 Dec;148(6):3527. doi: 10.1121/10.0002661.
Mathieu Lavandier, Christine R Mason, Lucas S Baltzell , Virginia Best. Individual differences in speech intelligibility at a cocktail party: A modeling perspective. J Acoust Soc Am. 2021 Aug;150(2):1076. doi: 10.1121/10.0005851.
Thibault Vicente, Jörg M Buchholz, Mathieu Lavandier. Modelling binaural unmasking and the intelligibility of speech in noise and reverberation for normal-hearing and hearing-impaired listeners. J Acoust Soc Am. 2021 Nov;150(5):3275. doi: 10.1121/10.0006736.
Mathieu Lavandier, Thibault Vicente, Luna Prud’homme. A series of SNR-based speech intelligibility models in the Auditory Modeling Toolbox. Acta Acustica, 6, 20.