Distributed-microphones based in-vehicle speech enhancement via sparse and low-rank spectrogram decomposition

被引:5
作者
Li, Xuliang [1 ,2 ]
Fan, Miao [1 ,2 ]
Liu, Liyang [1 ,2 ]
Li, Weifeng [1 ,2 ]
机构
[1] Tsinghua Univ, Grad Sch Shenzhen, Dept Elect Engn, Beijing, Peoples R China
[2] Shenzhen Key Lab Informat Sci & Technol, Shenzhen, Guangdong, Peoples R China
关键词
Distributed-microphones; Speech enhancement; Speech fusing; Sparse; Low-rank; PHASE; NOISE;
D O I
10.1016/j.specom.2017.12.008
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
In general, the in-vehicle speech enhancement is an application of the microphone array speech enhancement in particular acoustic environments. However, in this paper, we introduce a novel in-vehicle speech enhancement method based on distributed-microphones. The distributed-microphone signals have some features that the signals captured by microphone array do not have. Although distributed-microphones are not frequently used for speech enhancement, they can solve some practical problems, which cannot be solved by microphone array. In this paper, we propose a novel method using the signals acquired by distributed-microphones to enhance the speech corrupted by noise in-vehicle. The final enhanced speech is generated mainly by two steps. We first obtain the primary enhanced speech in each channel via sparse and low-rank spectrogram decomposition. Then based on the average improvements of segSNR (signal-to-noise ratio) and PESQ (perceptual evaluation of speech quality) in each channel, we fuse the primary enhanced speech in all channels into a single channel enhanced speech. In terms of PESQ and segSNR of the final enhanced speech, our approach outperforms several traditional approaches.
引用
收藏
页码:51 / 62
页数:12
相关论文
共 28 条
[1]   Phase-based dual-microphone robust speech enhancement [J].
Aarabi, P ;
Shi, G .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2004, 34 (04) :1763-1773
[2]   A signal subspace tracking algorithm for microphone array processing of speech [J].
Affes, S ;
Grenier, Y .
IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING, 1997, 5 (05) :425-437
[3]  
[Anonymous], 2010, 100920105055 ARXIV
[4]   A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking [J].
Arulampalam, MS ;
Maskell, S ;
Gordon, N ;
Clapp, T .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2002, 50 (02) :174-188
[5]   SUPPRESSION OF ACOUSTIC NOISE IN SPEECH USING SPECTRAL SUBTRACTION [J].
BOLL, SF .
IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING, 1979, 27 (02) :113-120
[6]  
Boluda Burguete V., 2015, THESIS
[7]  
Bruno M. G, 2004, AC SPEECH SIGN PROC, V2
[8]   Robust Principal Component Analysis? [J].
Candes, Emmanuel J. ;
Li, Xiaodong ;
Ma, Yi ;
Wright, John .
JOURNAL OF THE ACM, 2011, 58 (03)
[9]   Speech enhancement for non-stationary noise environments [J].
Cohen, I ;
Berdugo, B .
SIGNAL PROCESSING, 2001, 81 (11) :2403-2418
[10]   SPEECH ENHANCEMENT USING A MINIMUM MEAN-SQUARE ERROR LOG-SPECTRAL AMPLITUDE ESTIMATOR [J].
EPHRAIM, Y ;
MALAH, D .
IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING, 1985, 33 (02) :443-445