Speech Production in Challenging Listening Conditions
Noise, Ear Occlusion, Hearing Impairment, and Speech Production
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Summary
This project investigates how noise, ear occlusion, and hearing impairment shape speech production by altering self-auditory feedback. By developing and analyzing the Hearing-Integrated Bilingual Speech Corpus (HIBiSCus), the project provides new insights into speech motor control and supports innovations in hearables, audiology, and speech communication research.
Objectives
- Characterize how noise, ear occlusion, and hearing thresholds—individually and together—affect speech production.
- Develop the HIBiSCus corpus, a bilingual (English–French) speech database collected across different noise and ear occlusion conditions for various speech-rated tasks.
- Examine individual variability in the effect of noise, ear occlusion, and hearing threshold on speech level.
- Advance understanding of how hearing impairment influences speech level and its adaptation in different noise and ear occlusion conditions.
- Provide high-quality multimicrophone speech recordings for cross-disciplinary research on communication, hearing health, and hearables.
Timeline
| 2021 September | Start of project |
| 2024 June-December | Data collection |
| 2025 January-April | Data cleaning and analysis |
| 2025 May-August | Database and analysis on speech level: journal article written, with acceptance pending minor revision received in 2025 October. |
| Ongoing | Further analyses |
Approach
The methodology integrates experiments, corpus development, and statistical analysis:
- Speech was recorded in controlled acoustic conditions within an audiometric booth using multiple microphones (reference, in-ear, outer-ear).
- Listening conditions systematically varied across three noise levels (silent, 70, 85 dBA) and four ear occlusion states (open, simulated open, low occlusion, high occlusion).
- Participants performed three tasks: reading sentences, sustained vowel production, and picture description.
- Audiometric pure-tone hearing thresholds were measured to allow continuous modelling of hearing impairment.
- Linear mixed-effects modelling was used to evaluate how noise, occlusion, and hearing thresholds influence speech level and adaptation patterns.
Outcomes & Impact
- Creation of HIBiSCus, a French-English speech corpus examining noise, occlusion, and hearing thresholds together.
- New evidence on how hearing thresholds modulates the effect of noise and ear occlusion on speech level control.
- Insights supporting improved design of hearables, hearing aids, and communication technologies.
- Contributions to theories of speech motor control and auditory-feedback mechanisms.
- Open-access database enabling cross-disciplinary collaborations involving acoustics, audiology, speech science, and engineering.
People Involved
- Xinyi Zhang — Lead Researcher / PhD Student*
- Dr. Rachel Bouserhal — Supervisor (ÉTS, CIRMMT)*
- Dr. Ingrid Verduyckt — Co-investigator (Université de Montréal)
*CIRMMT Regular and student members
Partners
- The Research in Hearing Health and Assistive Devices (RHAD) Lab
- Centre for Interdisciplinary Research in Music, Media and Technology (CIRMMT)
- École de technologie supérieure (ÉTS)
- Université de Montréal — École d’orthophonie et d’audiologie
Granting Agencies / Funding Sponsors
- Natural Sciences and Engineering Research Council of Canada (NSERC - Discovery grant)
- Fonds de recherche du Québec's Master's training scholarship
- CIRMMT student award 2024-25
- ETS Marcelle Gauvreau Engineering Research Chair in Multimodal Health Monitoring and Early Disease Detection with Hearables
Resources
- Published paper: "Hearing-integrated bilingual speech corpus: a French-English corpus including hearables for studying speech production under challenging listening conditions". https://doi.org/10.1121/10.0042355
- Hearing-Integrated Bilingual Speech Corpus (HIBiSCus)
Keywords
Scientific/technological research, Speech production, Noise & ear occlusion, Hearing impairment, Auditory feedback
Learn More
- RHAD Lab website
- Google Scholar
- ORCiD
- LinkedIn Xinyi Zhang