A Supervised Approach to Global Signal-to-Noise Ratio Estimation for Whispered and Pathological Voices

Amir Hossein Poorjam, Max A Little, Jesper Rindom Jensen, Mads Græsbøll Christensen

    Research output: Chapter in Book/Published conference outputConference publication

    Abstract

    The presence of background noise in signals adversely affects the performance of many speech-based algorithms. Accurate estimation of signal-to-noise-ratio (SNR), as a measure of noise level in a signal, can help in compensating for noise effects. Most existing SNR estimation methods have been developed for normal speech and might not provide accurate estimation for special speech types such as whispered or disordered voices, particularly, when they are corrupted by non-stationary noises. In this paper, we first investigate the impact of stationary and non-stationary noise on the behavior of mel-frequency cepstral coefficients (MFCCs) extracted from normal, whispered and pathological voices. We demonstrate that, regardless of the speech type, the mean and the covariance of MFCCs are predictably modified by additive noise and the amount of change is related to the noise level. Then, we propose a new supervised method for SNR estimation which is based on a regression model trained on MFCCs of the noisy signals. Experimental results show that the proposed approach provides accurate estimation and consistent performance for various speech types under different noise conditions.
    Original languageEnglish
    Title of host publication2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    PublisherIEEE
    Pages296-300
    ISBN (Electronic)978-1-5386-4658-8
    ISBN (Print)978-1-5386-4659-5
    DOIs
    Publication statusPublished - 13 Sept 2018
    Event2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Calgary, Canada
    Duration: 15 Apr 201820 Apr 2018

    Publication series

    Name2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    PublisherIEEE
    ISSN (Electronic)2379-190X

    Conference

    Conference2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    Country/TerritoryCanada
    CityCalgary
    Period15/04/1820/04/18

    Bibliographical note

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