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    ASIA unversity > 資訊學院 > 資訊傳播學系 > 期刊論文 >  Item 310904400/102188

    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/102188

    Title: Estimation of Noise Magnitude for Speech Denoising Using Minima-Controlled-Recursive-Averaging Algorithm Adapted by Harmonic Properties
    Authors: 陸清達;Lu, Ching-Ta;*;Le, Chung-Lin;Lei, Chung-Lin;沈俊宏;SHEN, JUN-HONG;王玲玲;Wang, Ling-Ling;Tseng, Kun-Fu
    Contributors: 資訊傳播學系
    Date: 2016-12
    Issue Date: 2017-03-01 14:48:06 (UTC+8)
    Abstract: Abstract
    The accuracy of noise estimation is important for the performance of a speech denoising system. Most noise estimators suffer from either overestimation or underestimation on the noise level. An overestimate on noise magnitude will cause serious speech distortion for speech denoising. Conversely, a great quantity of residual noise will occur when the noise magnitude is underestimated. Accurately estimating noise magnitude is important for speech denoising. This study proposes employing variable segment length for noise tracking and variable thresholds for the determination of speech presence probability, resulting in the performance improvement for a minima-controlled-recursive-averaging (MCRA) algorithm in noise estimation. Initially, the fundamental frequency was estimated to determine whether a frame is a vowel. In the case of a vowel frame, the increment of segment lengths and the decrement of threshold for speech presence were performed which resulted in underestimating the level of noise magnitude. Accordingly, the speech distortion is reduced in denoised speech. On the contrary, the segment length decreases rapidly in noise-dominant regions. This enables the noise estimate to update quickly and the noise variation to track well, yielding interference noise being removed effectively through the process of speech denoising. Experimental results show that the proposed approach has been effective in improving the performance of the MCRA algorithm by preserving the weak vowels and consonants. The denoising performance is therefore improved.
    Relation: Applied Sciences-Basel
    Appears in Collections:[資訊傳播學系] 期刊論文

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