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An algorithm to improve speech recognition in noise for hearing-impaired listeners.
J Acoust Soc Am. 2013 Oct; 134(4):3029-38.JA

Abstract

Despite considerable effort, monaural (single-microphone) algorithms capable of increasing the intelligibility of speech in noise have remained elusive. Successful development of such an algorithm is especially important for hearing-impaired (HI) listeners, given their particular difficulty in noisy backgrounds. In the current study, an algorithm based on binary masking was developed to separate speech from noise. Unlike the ideal binary mask, which requires prior knowledge of the premixed signals, the masks used to segregate speech from noise in the current study were estimated by training the algorithm on speech not used during testing. Sentences were mixed with speech-shaped noise and with babble at various signal-to-noise ratios (SNRs). Testing using normal-hearing and HI listeners indicated that intelligibility increased following processing in all conditions. These increases were larger for HI listeners, for the modulated background, and for the least-favorable SNRs. They were also often substantial, allowing several HI listeners to improve intelligibility from scores near zero to values above 70%.

Authors+Show Affiliations

Department of Speech and Hearing Science, and Center for Cognitive and Brain Sciences, The Ohio State University, Columbus, Ohio 43210.No affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

Language

eng

PubMed ID

24116438

Citation

Healy, Eric W., et al. "An Algorithm to Improve Speech Recognition in Noise for Hearing-impaired Listeners." The Journal of the Acoustical Society of America, vol. 134, no. 4, 2013, pp. 3029-38.
Healy EW, Yoho SE, Wang Y, et al. An algorithm to improve speech recognition in noise for hearing-impaired listeners. J Acoust Soc Am. 2013;134(4):3029-38.
Healy, E. W., Yoho, S. E., Wang, Y., & Wang, D. (2013). An algorithm to improve speech recognition in noise for hearing-impaired listeners. The Journal of the Acoustical Society of America, 134(4), 3029-38. https://doi.org/10.1121/1.4820893
Healy EW, et al. An Algorithm to Improve Speech Recognition in Noise for Hearing-impaired Listeners. J Acoust Soc Am. 2013;134(4):3029-38. PubMed PMID: 24116438.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - An algorithm to improve speech recognition in noise for hearing-impaired listeners. AU - Healy,Eric W, AU - Yoho,Sarah E, AU - Wang,Yuxuan, AU - Wang,DeLiang, PY - 2013/10/15/entrez PY - 2013/10/15/pubmed PY - 2014/5/31/medline SP - 3029 EP - 38 JF - The Journal of the Acoustical Society of America JO - J Acoust Soc Am VL - 134 IS - 4 N2 - Despite considerable effort, monaural (single-microphone) algorithms capable of increasing the intelligibility of speech in noise have remained elusive. Successful development of such an algorithm is especially important for hearing-impaired (HI) listeners, given their particular difficulty in noisy backgrounds. In the current study, an algorithm based on binary masking was developed to separate speech from noise. Unlike the ideal binary mask, which requires prior knowledge of the premixed signals, the masks used to segregate speech from noise in the current study were estimated by training the algorithm on speech not used during testing. Sentences were mixed with speech-shaped noise and with babble at various signal-to-noise ratios (SNRs). Testing using normal-hearing and HI listeners indicated that intelligibility increased following processing in all conditions. These increases were larger for HI listeners, for the modulated background, and for the least-favorable SNRs. They were also often substantial, allowing several HI listeners to improve intelligibility from scores near zero to values above 70%. SN - 1520-8524 UR - https://www.unboundmedicine.com/medline/citation/24116438/An_algorithm_to_improve_speech_recognition_in_noise_for_hearing_impaired_listeners_ L2 - https://doi.org/10.1121/1.4820893 DB - PRIME DP - Unbound Medicine ER -