Assessment of broadband SNR estimation for hearing aid applications

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Abstract

An accurate estimation of the broadband input signal-to-noise ratio (SNR) is a prerequisite for many hearing-aid algorithms. An extensive comparison of three SNR estimation algorithms was performed. Moreover, the influence of the duration of the analysis window on the SNR estimation performance was systematically investigated.
The most accurate approach utilized an estimation of the clean speech power spectral density (PSD) and the noisy speech power across a sliding window of 1280 ms and achieved an total SNR estimation error below 3 dB across a wide variety of background noises and input SNRs
Original languageEnglish
Title of host publicationProceedings of ICASSP 2017
PublisherIEEE
Publication date2017
Pages231-235
ISBN (Print)978-1-5090-4117-6
DOIs
Publication statusPublished - 2017
Event42nd IEEE International Conference on Acoustics, Speech and Signal Processing: The internet of signals - Hilton New Orleans Riverside, New Orleans, United States
Duration: 5 Mar 20179 Mar 2017
Conference number: 42
http://www.ieee-icassp2017.org/

Conference

Conference42nd IEEE International Conference on Acoustics, Speech and Signal Processing
Number42
LocationHilton New Orleans Riverside
CountryUnited States
CityNew Orleans
Period05/03/201709/03/2017
Internet address

Keywords

  • Signal-to-noise ratio estimation
  • Noise power estimation
  • Hearing-aid algorithms

Cite this

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title = "Assessment of broadband SNR estimation for hearing aid applications",
abstract = "An accurate estimation of the broadband input signal-to-noise ratio (SNR) is a prerequisite for many hearing-aid algorithms. An extensive comparison of three SNR estimation algorithms was performed. Moreover, the influence of the duration of the analysis window on the SNR estimation performance was systematically investigated.The most accurate approach utilized an estimation of the clean speech power spectral density (PSD) and the noisy speech power across a sliding window of 1280 ms and achieved an total SNR estimation error below 3 dB across a wide variety of background noises and input SNRs",
keywords = "Signal-to-noise ratio estimation, Noise power estimation, Hearing-aid algorithms",
author = "Tobias May and Borys Kowalewski and Michal Fereczkowski and Ewen MacDonald",
year = "2017",
doi = "10.1109/ICASSP.2017.7952152",
language = "English",
isbn = "978-1-5090-4117-6",
pages = "231--235",
booktitle = "Proceedings of ICASSP 2017",
publisher = "IEEE",
address = "United States",

}

May, T, Kowalewski, B, Fereczkowski, M & MacDonald, E 2017, Assessment of broadband SNR estimation for hearing aid applications. in Proceedings of ICASSP 2017. IEEE, pp. 231-235, 42nd IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, United States, 05/03/2017. https://doi.org/10.1109/ICASSP.2017.7952152

Assessment of broadband SNR estimation for hearing aid applications. / May, Tobias; Kowalewski, Borys; Fereczkowski, Michal; MacDonald, Ewen.

Proceedings of ICASSP 2017. IEEE, 2017. p. 231-235.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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AB - An accurate estimation of the broadband input signal-to-noise ratio (SNR) is a prerequisite for many hearing-aid algorithms. An extensive comparison of three SNR estimation algorithms was performed. Moreover, the influence of the duration of the analysis window on the SNR estimation performance was systematically investigated.The most accurate approach utilized an estimation of the clean speech power spectral density (PSD) and the noisy speech power across a sliding window of 1280 ms and achieved an total SNR estimation error below 3 dB across a wide variety of background noises and input SNRs

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DO - 10.1109/ICASSP.2017.7952152

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