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A New Speech Enhancement Method for Fan Noise

Published: 28 April 2018 Publication History

Abstract

In addition to the steady background noise, there are many non-stationary harmonic noises in the speech under the influence of fan noise, which has the characteristics of mutation and randomness.None of the existing speech enhancement algorithms can suppress the noise very well. In order to remove the non-stationary harmonic noise in the environment, improve the signal to noise ratio, and reduce the distortion of the speech after denoising, this paper proposes a new speech enhancement algorithm:1.A new threshold decision method is designed to achieve the effect of de harmonic. 2. Eliminating sudden noise of environment by noise estimation method. Experiments show that this algorithm not only improves the noise suppression ability in the non-speech zone, but also the denoising effect is better than traditional speech enhancement algorithm.

References

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Yin Dong. Summary of speech enhancement algorithm and performance analysis. Speech technology, 2015.5

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  1. A New Speech Enhancement Method for Fan Noise

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    ICMSSP '18: Proceedings of the 3rd International Conference on Multimedia Systems and Signal Processing
    April 2018
    168 pages
    ISBN:9781450364577
    DOI:10.1145/3220162
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 28 April 2018

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    Author Tags

    1. Noise estimation
    2. Speech enhancement
    3. Threshold decision

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