Assessment of broadband SNR estimation for hearing aid applications

Tobias May, Borys Kowalewski, Michal Fereczkowski, Ewen MacDonald

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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
    Event2017 IEEE International Conference on Acoustics, Speech and Signal Processing - Hilton New Orleans Riverside, New Orleans, United States
    Duration: 5 Mar 20179 Mar 2017
    Conference number: 42
    http://www.ieee-icassp2017.org/

    Conference

    Conference2017 IEEE International Conference on Acoustics, Speech and Signal Processing
    Number42
    LocationHilton New Orleans Riverside
    Country/TerritoryUnited States
    CityNew Orleans
    Period05/03/201709/03/2017
    Internet address

    Keywords

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

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