Address: 3105 Bondurant Hall
- Ph.D., Speech, Language, and Hearing Sciences; University of Connecticut (2020)
- Au.D.; University of Connecticut (2020)
- B.A., Psychology; Speech, Language and Hearing Sciences; University of Connecticut (2014)
Pediatric Hearing Assessment (SPHS 811)
Speech perception; cochlear implantation; perceptual learning of speech; spoken language development
American Speech-Language-Hearing Association
My research program examines how listeners access and understand spoken language across development, with a focus on the plasticity mechanisms that support rehabilitation for cochlear implant users. My overarching research goal is to optimize the rehabilitation process for listeners with hearing loss and to provide evidence-based training recommendations for clinicians. Towards this goal, I am the principal investigator of the ALLears (Auditory Language Learning) Laboratory at UNC where I use behavioral and eye-tracking methodology to examine spoken language processing.
Drouin, J.R. & Theodore, R.M. (2022). Many tasks, same outcome: Role of training task on learning and maintenance of noise-vocoded speech. Journal of the Acoustical Society of America.
Drouin, J.R. & Theodore, R.M. (2020). Leveraging interdisciplinary perspectives to optimize auditory training for cochlear implant users. Language & Linguistics Compass, 14(9), e12394.
Drouin, J.R. & Theodore, R.M. (2018). Lexically guided perceptual learning is robust to task-based changes in listening strategy. Journal of the Acoustical Society of America, 144(2), 1089 – 1099.
Drouin, J.R. & Theodore, R.M. (2016). Lexically guided perceptual learning of internal phonetic category structure. Journal of the Acoustical Society of America Express Letters, 140(4), EL307 – EL313.
Drouin, J.R., Monto, N.R., & Theodore, R.M. (2017). Talker-specificity effects in spoken language processing: Now you seem them, now you don’t. The speech processing lexicon: Neurocognitive and behavioral approaches, 22, (pp. 107 – 128).
Desoto, A., Santos, E., Liri, F., Faller, K., Heng, D., Dodd, J., George, K., & Drouin, J. (2022). Predicting Audio Training Learning Outcomes Using EEG Data and KNN Modeling. 2022 IEEE Annual Computing and Communication Works and Conference (CCWC).
Liri, F.X., Desoto, A., Catalan, W., George, K., Faller, J.F., Drouin, J.R. (2022). Monitoring Audio Training Learning Outcomes. 2022 IEEE Annual Computing and Communication Works and Conference (CCWC).