Two-Microphone Noise Reduction Using Spatial Information-Based Spectral Amplitude Estimation

Kai LI; Yanmeng GUO; Qiang FU; Junfeng LI; Yonghong YAN

doi:10.1587/transinf.E95.D.1454

Two-Microphone Noise Reduction Using Spatial Information-Based Spectral Amplitude Estimation

Kai LI, Yanmeng GUO, Qiang FU, Junfeng LI, Yonghong YAN

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Traditional two-microphone noise reduction algorithms to deal with highly nonstationary directional noises generally use the direction of arrival or phase difference information. The performance of these algorithms deteriorate when diffuse noises coexist with nonstationary directional noises in realistic adverse environments. In this paper, we present a two-channel noise reduction algorithm using a spatial information-based speech estimator and a spatial-information-controlled soft-decision noise estimator to improve the noise reduction performance in realistic non-stationary noisy environments. A target presence probability estimator based on Bayes rules using both phase difference and magnitude squared coherence is proposed for soft-decision of noise estimation, so that they can share complementary advantages when both directional noises and diffuse noises are present. Performances of the proposed two-microphone noise reduction algorithm are evaluated by noise reduction, log-spectral distance (LSD) and word recognition rate (WRR) of a distant-talking ASR system in a real room's noisy environment. Experimental results show that the proposed algorithm achieves better noises suppression without further distorting the desired signal components over the comparative dual-channel noise reduction algorithms.

Publication: IEICE TRANSACTIONS on Information Vol.E95-D No.5 pp.1454-1464

Publication Date: 2012/05/01

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Online ISSN: 1745-1361

DOI: 10.1587/transinf.E95.D.1454

Type of Manuscript: PAPER

Category: Speech and Hearing

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Kai LI, Yanmeng GUO, Qiang FU, Junfeng LI, Yonghong YAN, "Two-Microphone Noise Reduction Using Spatial Information-Based Spectral Amplitude Estimation" in IEICE TRANSACTIONS on Information, vol. E95-D, no. 5, pp. 1454-1464, May 2012, doi: 10.1587/transinf.E95.D.1454.
Abstract: Traditional two-microphone noise reduction algorithms to deal with highly nonstationary directional noises generally use the direction of arrival or phase difference information. The performance of these algorithms deteriorate when diffuse noises coexist with nonstationary directional noises in realistic adverse environments. In this paper, we present a two-channel noise reduction algorithm using a spatial information-based speech estimator and a spatial-information-controlled soft-decision noise estimator to improve the noise reduction performance in realistic non-stationary noisy environments. A target presence probability estimator based on Bayes rules using both phase difference and magnitude squared coherence is proposed for soft-decision of noise estimation, so that they can share complementary advantages when both directional noises and diffuse noises are present. Performances of the proposed two-microphone noise reduction algorithm are evaluated by noise reduction, log-spectral distance (LSD) and word recognition rate (WRR) of a distant-talking ASR system in a real room's noisy environment. Experimental results show that the proposed algorithm achieves better noises suppression without further distorting the desired signal components over the comparative dual-channel noise reduction algorithms.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E95.D.1454/_p

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@ARTICLE{e95-d_5_1454,
author={Kai LI, Yanmeng GUO, Qiang FU, Junfeng LI, Yonghong YAN, },
journal={IEICE TRANSACTIONS on Information},
title={Two-Microphone Noise Reduction Using Spatial Information-Based Spectral Amplitude Estimation},
year={2012},
volume={E95-D},
number={5},
pages={1454-1464},
abstract={Traditional two-microphone noise reduction algorithms to deal with highly nonstationary directional noises generally use the direction of arrival or phase difference information. The performance of these algorithms deteriorate when diffuse noises coexist with nonstationary directional noises in realistic adverse environments. In this paper, we present a two-channel noise reduction algorithm using a spatial information-based speech estimator and a spatial-information-controlled soft-decision noise estimator to improve the noise reduction performance in realistic non-stationary noisy environments. A target presence probability estimator based on Bayes rules using both phase difference and magnitude squared coherence is proposed for soft-decision of noise estimation, so that they can share complementary advantages when both directional noises and diffuse noises are present. Performances of the proposed two-microphone noise reduction algorithm are evaluated by noise reduction, log-spectral distance (LSD) and word recognition rate (WRR) of a distant-talking ASR system in a real room's noisy environment. Experimental results show that the proposed algorithm achieves better noises suppression without further distorting the desired signal components over the comparative dual-channel noise reduction algorithms.},
keywords={},
doi={10.1587/transinf.E95.D.1454},
ISSN={1745-1361},
month={May},}

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TY - JOUR
TI - Two-Microphone Noise Reduction Using Spatial Information-Based Spectral Amplitude Estimation
T2 - IEICE TRANSACTIONS on Information
SP - 1454
EP - 1464
AU - Kai LI
AU - Yanmeng GUO
AU - Qiang FU
AU - Junfeng LI
AU - Yonghong YAN
PY - 2012
DO - 10.1587/transinf.E95.D.1454
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2012
AB - Traditional two-microphone noise reduction algorithms to deal with highly nonstationary directional noises generally use the direction of arrival or phase difference information. The performance of these algorithms deteriorate when diffuse noises coexist with nonstationary directional noises in realistic adverse environments. In this paper, we present a two-channel noise reduction algorithm using a spatial information-based speech estimator and a spatial-information-controlled soft-decision noise estimator to improve the noise reduction performance in realistic non-stationary noisy environments. A target presence probability estimator based on Bayes rules using both phase difference and magnitude squared coherence is proposed for soft-decision of noise estimation, so that they can share complementary advantages when both directional noises and diffuse noises are present. Performances of the proposed two-microphone noise reduction algorithm are evaluated by noise reduction, log-spectral distance (LSD) and word recognition rate (WRR) of a distant-talking ASR system in a real room's noisy environment. Experimental results show that the proposed algorithm achieves better noises suppression without further distorting the desired signal components over the comparative dual-channel noise reduction algorithms.
ER -