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Department of Health Sciences

Research

Speech Adaptation & Translational (Re)habilitation

Current research efforts are focused on contributing to both basic models of the speech perception mechanism and clinical recommendations for optimizing spoken language outcomes for individuals with hearing loss. We use an interdisciplinary framework to explore the perceptual, cognitive, and neural basis of spoken language processing and speech learning. 

Student researcher in lab

Both normal hearing listeners and listeners with hearing loss encounter situations that lead to speech understanding difficulties (e.g., bad cellphone reception; accented speech; noisy environments), yet often with a bit of experience, listeners come to comprehend those signals rather quickly. For listeners with hearing loss, the use of devices like hearing aids or cochlear implants supports access to the auditory signal of speech. However, adapting to new devices like a hearing aid or cochlear implant can be a process that takes time and individual listeners vary in terms of speech intelligibility benefits. Research in the lab is particularly interested in the adaptation process that supports speech learning in listeners with and without hearing loss.

Research in the lab generally falls in the following broad themes:

  • Explicating the role of experience (passive or active auditory training) on adaptation to novel speech signals
  • Leveraging speech learning to maximize benefit for individuals adapting to cochlear implants or hearing aids
  • Characterizing differences in speech learning outcomes and needs between pediatric and adult listeners with hearing loss
  • Exploring the downstream effects of improved speech adaptation on cognitive and physiologic mechanisms

Lab Publications & Presentations

2024

  • Drouin, J.R. & Flores, S. (in press). Effects of training length on adaptation to noise-vocoded speech. Journal of the Acoustical Society of America. PREPRINT/CODE
  • Drouin, J.R., Putnam, L., Davis, C.P. (in revision). Malleability of the lexical bias effect for degraded speech. PREPRINT/CODE
  • Drouin, J.R. & Davis, C.P. (in revision). Individual differences in visual pattern completion predict adaptation to degraded speech. PREPRINT/CODE 

2023

  • Drouin, J. R., & Rojas, J. A. (2023). Influence of face masks on recalibration of phonetic categories. Attention, Perception, & Psychophysics, 1-18.
  • Drouin, J. R., Zysk, V. A., Myers, E. B., & Theodore, R. M. (2023). Sleep-Based Memory Consolidation Stabilizes Perceptual Learning of Noise-Vocoded Speech. Journal of Speech, Language, and Hearing Research, 66(2), 720-734.

  • Flores, S. & Drouin, J.R. (2023). Effects of Training Length on Adaptation to Noise-vocoded Speech. Presented at the 2023 American Speech Language and Hearing Association Conference. Boston, MA.

  • Drouin, J.R. (July 2023). Engaging cochlear implant users using online methods. Invited talk to be presented at the 2023 BeOnline Conference.

  • Drouin, J.R. & Davis, C.P. (2023). The lexical bias effect in adult cochlear implant users. Presented at the 2023 American Auditory Society Conference. Scottsdale, AZ.

2022

  • Drouin, J. R., & Theodore, R. M. (2022). Many tasks, same outcome: Role of training task on learning and maintenance of noise-vocoded speech. The Journal of the Acoustical Society of America, 152(2), 981-993. 
  • Desoto, A., Santos, E., Liri, F., Faller, K., Heng, D., Dodd, J., … & Drouin, J. (2022, June). Predicting Audio Training Learning Outcomes Using EEG Data and KNN Modeling. In 2022 IEEE World AI IoT Congress (AIIoT) (pp. 466-470). IEEE.
  • Liri, F., Desoto, A., Catalan, W., George, K., Faller, K., & Drouin, J. (2022, January). Monitoring Audio Training Learning Outcomes with EEG Data. In 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 0545-0551). IEEE.

  • Mosley, C. & Drouin, J.R. Designing evidence-based telehealth aural rehabilitation protocols. (Nov. 2022). Master class presented at the 2022 American Speech Language and Hearing Association Conference. New Orleans, LA.

  • Putnam, L. & Drouin, J.R. (2022). Malleability of the Lexical Bias Effect for Noise-Vocoded Speech. Presented at the 2022 American Speech Language and Hearing Association Conference. New Orleans, LA.

2020

  • Drouin, J. R., & Theodore, R. M. (2020). Leveraging interdisciplinary perspectives to optimize auditory training for cochlear implant users. Language and Linguistics Compass, 14(9), e12394.

2018

2017

2016

 

*Individuals interested in accessing published lab articles should email Dr. Julia Drouin (julia_drouin@med.unc.edu). Preprints, data, and code are available on the Open Science Framework as appropriate.