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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kami telah mencadangkan kaedah pengurangan hingar berdasarkan sistem pembinaan semula hingar (NRS). NRS menggunakan penapis ralat ramalan linear (LPEF) dan penapis pembinaan semula hingar (NRF) yang menganggarkan hingar latar belakang melalui pengenalan sistem. Sekiranya saiz langkah tetap untuk mengemas kini pekali paip NRF digunakan, adalah sukar untuk mengurangkan bunyi latar belakang sambil mengekalkan kualiti tinggi pertuturan yang dipertingkatkan. Untuk menyelesaikan masalah, saiz langkah berubah-ubah dicadangkan. Ia menggunakan korelasi silang antara isyarat input dan isyarat pertuturan yang dipertingkatkan. Dalam bahagian pertuturan, saiz langkah berubah menjadi kecil supaya tidak menganggarkan pertuturan, sebaliknya, besar untuk menjejak bunyi latar belakang dalam bahagian bukan pertuturan.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Salinan
Naoto SASAOKA, Masatoshi WATANABE, Yoshio ITOH, Kensaku FUJII, "A Variable Step Size Algorithm for Speech Noise Reduction Method Based on Noise Reconstruction System" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 1, pp. 244-251, January 2009, doi: 10.1587/transfun.E92.A.244.
Abstract: We have proposed a noise reduction method based on a noise reconstruction system (NRS). The NRS uses a linear prediction error filter (LPEF) and a noise reconstruction filter (NRF) which estimates background noise by system identification. In case a fixed step size for updating tap coefficients of the NRF is used, it is difficult to reduce background noise while maintaining the high quality of enhanced speech. In order to solve the problem, a variable step size is proposed. It makes use of cross-correlation between an input signal and an enhanced speech signal. In a speech section, a variable step size becomes small so as not to estimate speech, on the other hand, large to track the background noise in a non-speech section.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.244/_p
Salinan
@ARTICLE{e92-a_1_244,
author={Naoto SASAOKA, Masatoshi WATANABE, Yoshio ITOH, Kensaku FUJII, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Variable Step Size Algorithm for Speech Noise Reduction Method Based on Noise Reconstruction System},
year={2009},
volume={E92-A},
number={1},
pages={244-251},
abstract={We have proposed a noise reduction method based on a noise reconstruction system (NRS). The NRS uses a linear prediction error filter (LPEF) and a noise reconstruction filter (NRF) which estimates background noise by system identification. In case a fixed step size for updating tap coefficients of the NRF is used, it is difficult to reduce background noise while maintaining the high quality of enhanced speech. In order to solve the problem, a variable step size is proposed. It makes use of cross-correlation between an input signal and an enhanced speech signal. In a speech section, a variable step size becomes small so as not to estimate speech, on the other hand, large to track the background noise in a non-speech section.},
keywords={},
doi={10.1587/transfun.E92.A.244},
ISSN={1745-1337},
month={January},}
Salinan
TY - JOUR
TI - A Variable Step Size Algorithm for Speech Noise Reduction Method Based on Noise Reconstruction System
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 244
EP - 251
AU - Naoto SASAOKA
AU - Masatoshi WATANABE
AU - Yoshio ITOH
AU - Kensaku FUJII
PY - 2009
DO - 10.1587/transfun.E92.A.244
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2009
AB - We have proposed a noise reduction method based on a noise reconstruction system (NRS). The NRS uses a linear prediction error filter (LPEF) and a noise reconstruction filter (NRF) which estimates background noise by system identification. In case a fixed step size for updating tap coefficients of the NRF is used, it is difficult to reduce background noise while maintaining the high quality of enhanced speech. In order to solve the problem, a variable step size is proposed. It makes use of cross-correlation between an input signal and an enhanced speech signal. In a speech section, a variable step size becomes small so as not to estimate speech, on the other hand, large to track the background noise in a non-speech section.
ER -