Eric W. Healy, Ph.D.
Affiliations: | Ohio State University, Columbus, Columbus, OH |
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"Eric Healy"Mean distance: 106866
Cross-listing: CSD Tree
Collaborators
Sign in to add collaborator| Etienne Gaudrain | collaborator | Université Lyon 1, Université de Lyon |
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Publications
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| Healy EW, Johnson EM, Pandey A, et al. (2023) Progress made in the efficacy and viability of deep-learning-based noise reduction. The Journal of the Acoustical Society of America. 153: 2751 |
| Borrie SA, Yoho SE, Healy EW, et al. (2023) The Application of Time-Frequency Masking To Improve Intelligibility of Dysarthric Speech in Background Noise. Journal of Speech, Language, and Hearing Research : Jslhr. 1-14 |
| Carter BL, Apoux F, Healy EW. (2022) The Influence of Noise Type and Semantic Predictability on Word Recall in Older Listeners and Listeners With Hearing Impairment. Journal of Speech, Language, and Hearing Research : Jslhr. 1-18 |
| Healy EW, Taherian H, Johnson EM, et al. (2021) A causal and talker-independent speaker separation/dereverberation deep learning algorithm: Cost associated with conversion to real-time capable operation. The Journal of the Acoustical Society of America. 150: 3976 |
| Healy EW, Johnson EM, Delfarah M, et al. (2021) Deep learning based speaker separation and dereverberation can generalize across different languages to improve intelligibility. The Journal of the Acoustical Society of America. 150: 2526 |
| Healy EW, Tan K, Johnson EM, et al. (2021) An effectively causal deep learning algorithm to increase intelligibility in untrained noises for hearing-impaired listeners. The Journal of the Acoustical Society of America. 149: 3943 |
| Fogerty D, Sevich VA, Healy EW. (2020) Spectro-temporal glimpsing of speech in noise: Regularity and coherence of masking patterns reduces uncertainty and increases intelligibility. The Journal of the Acoustical Society of America. 148: 1552 |
| Healy EW, Johnson EM, Delfarah M, et al. (2020) A talker-independent deep learning algorithm to increase intelligibility for hearing-impaired listeners in reverberant competing talker conditions. The Journal of the Acoustical Society of America. 147: 4106 |
| Healy EW, Vasko JL, Wang D. (2019) The optimal threshold for removing noise from speech is similar across normal and impaired hearing-a time-frequency masking study. The Journal of the Acoustical Society of America. 145: EL581 |
| Healy EW, Delfarah M, Johnson EM, et al. (2019) A deep learning algorithm to increase intelligibility for hearing-impaired listeners in the presence of a competing talker and reverberation. The Journal of the Acoustical Society of America. 145: 1378 |