The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
A subtração espectral é comumente usada para aprimoramento de fala em um sistema de canal único devido à simplicidade de sua implementação. No entanto, este algoritmo introduz ruído perceptualmente musical enquanto suprime o ruído de fundo. Propomos neste artigo uma abordagem baseada em wavelets para suprimir o ruído de fundo para aprimoramento de fala em um sistema de canal único. A transformada de pacote wavelet, que emula o sistema auditivo humano, é usada para decompor o sinal ruidoso em bandas críticas. O limiar de wavelet é então ajustado temporalmente com a potência do ruído por estimativa de ruído adaptada ao tempo. O algoritmo proposto pode suprimir eficientemente o ruído e, ao mesmo tempo, reduzir a distorção da fala. Resultados experimentais, incluindo várias medições objetivas, mostram que o algoritmo baseado em wavelet proposto supera a subtração espectral e outras abordagens de eliminação de ruído baseadas em wavelet para aprimoramento de fala em ambientes de ruído não estacionários.
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Sheau-Fang LEI, Ying-Kai TUNG, "Wavelet-Based Speech Enhancement Using Time-Adapted Noise Estimation" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 9, pp. 2555-2563, September 2008, doi: 10.1093/ietfec/e91-a.9.2555.
Abstract: Spectral subtraction is commonly used for speech enhancement in a single channel system because of the simplicity of its implementation. However, this algorithm introduces perceptually musical noise while suppressing the background noise. We propose a wavelet-based approach in this paper for suppressing the background noise for speech enhancement in a single channel system. The wavelet packet transform, which emulates the human auditory system, is used to decompose the noisy signal into critical bands. Wavelet thresholding is then temporally adjusted with the noise power by time-adapted noise estimation. The proposed algorithm can efficiently suppress the noise while reducing speech distortion. Experimental results, including several objective measurements, show that the proposed wavelet-based algorithm outperforms spectral subtraction and other wavelet-based denoising approaches for speech enhancement for nonstationary noise environments.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.9.2555/_p
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@ARTICLE{e91-a_9_2555,
author={Sheau-Fang LEI, Ying-Kai TUNG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Wavelet-Based Speech Enhancement Using Time-Adapted Noise Estimation},
year={2008},
volume={E91-A},
number={9},
pages={2555-2563},
abstract={Spectral subtraction is commonly used for speech enhancement in a single channel system because of the simplicity of its implementation. However, this algorithm introduces perceptually musical noise while suppressing the background noise. We propose a wavelet-based approach in this paper for suppressing the background noise for speech enhancement in a single channel system. The wavelet packet transform, which emulates the human auditory system, is used to decompose the noisy signal into critical bands. Wavelet thresholding is then temporally adjusted with the noise power by time-adapted noise estimation. The proposed algorithm can efficiently suppress the noise while reducing speech distortion. Experimental results, including several objective measurements, show that the proposed wavelet-based algorithm outperforms spectral subtraction and other wavelet-based denoising approaches for speech enhancement for nonstationary noise environments.},
keywords={},
doi={10.1093/ietfec/e91-a.9.2555},
ISSN={1745-1337},
month={September},}
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TY - JOUR
TI - Wavelet-Based Speech Enhancement Using Time-Adapted Noise Estimation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2555
EP - 2563
AU - Sheau-Fang LEI
AU - Ying-Kai TUNG
PY - 2008
DO - 10.1093/ietfec/e91-a.9.2555
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2008
AB - Spectral subtraction is commonly used for speech enhancement in a single channel system because of the simplicity of its implementation. However, this algorithm introduces perceptually musical noise while suppressing the background noise. We propose a wavelet-based approach in this paper for suppressing the background noise for speech enhancement in a single channel system. The wavelet packet transform, which emulates the human auditory system, is used to decompose the noisy signal into critical bands. Wavelet thresholding is then temporally adjusted with the noise power by time-adapted noise estimation. The proposed algorithm can efficiently suppress the noise while reducing speech distortion. Experimental results, including several objective measurements, show that the proposed wavelet-based algorithm outperforms spectral subtraction and other wavelet-based denoising approaches for speech enhancement for nonstationary noise environments.
ER -