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Single-Channel Audio Source Separation with NMF: Divergences, Constraints and Algorithms Read chapter Read first chapter

2018 | OriginalPaper | Chapter

13. Musical-Noise-Free Blind Speech Extraction Based on Higher-Order Statistics Analysis

Authors : Hiroshi Saruwatari, Ryoichi Miyazaki

Published in: Audio Source Separation

Publisher: Springer International Publishing

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Abstract

In this chapter, we introduce a musical-noise-free blind speech extraction method using a microphone array for application to nonstationary noise. In the recent noise reduction study, it was found that optimized iterative spectral subtraction (SS) results in speech enhancement with almost no musical noise generation, but this method is valid only for stationary noise. The method presented in this chapter consists of iterative blind dynamic noise estimation by, e.g., independent component analysis (ICA) or multichannel Wiener filtering, and musical-noise-free speech extraction by modified iterative SS, where multiple iterative SS is applied to each channel while maintaining the multichannel property reused for the dynamic noise estimators. Also, in relation to the method, we discuss the justification of applying ICA to signals nonlinearly distorted by SS. From objective and subjective evaluations simulating a real-world hands-free speech communication system, we reveal that the method outperforms the conventional speech enhancement methods.

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previous chapter Multimicrophone MMSE-Based Speech Source Separation
next chapter Audio-Visual Source Separation with Alternating Diffusion Maps
Appendix
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Literature
1.
S.F. Boll, Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans. Acoust. Speech Signal Process. 27(2), 113–120 (1979)CrossRef
2.
M. Berouti, R. Schwartz, J. Makhoul, Enhancement of speech corrupted by acoustic noise, in Proceeding of ICASSP (1979), pp. 208–211
3.
R. McAulay, M. Malpass, Speech enhancement using a soft-decision noise suppression filter. IEEE Trans. Acoust. Speech Signal Process. 28(2), 137–145 (1980)CrossRef
4.
R. Martin, Spectral subtraction based on minimum statistics, in Proceeding of EUSIPCO (1994), pp. 1182–1185
5.
P.C. Loizou, Speech Enhancement Theory and Practice (CRC Press, Taylor & Francis Group FL, 2007)
6.
Y. Ephraim, D. Malah, Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator. IEEE Trans. Acoust. Speech Signal Process. 32(6), 1109–1121 (1984)CrossRef
7.
Y. Ephraim, D. Malah, Speech enhancement using a minimum mean square error log-spectral amplitude estimator. IEEE Trans. Acoust. Speech Signal Process. 33(2), 443–445 (1985)CrossRef
8.
T. Lotter, P. Vary, Speech enhancement by MAP spectral amplitude estimation using a super-Gaussian speech model. EURASIP J. Appl. Signal Process. 2005, 1110–1126 (2005)MATH
9.
O. Cappe, Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor. IEEE Trans. Speech Audio Process. 2(2), 345–349 (1994)CrossRef
10.
Z. Goh, K.-C. Tan, B. Tan, Postprocessing method for suppressing musical noise generated by spectral subtraction. IEEE Trans. Speech Audio Process. 6(3), 287–292 (1998)CrossRef
11.
Y. Uemura, Y. Takahashi, H. Saruwatari, K. Shikano, K. Kondo, Automatic optimization scheme of spectral subtraction based on musical noise assessment via higher-order statistics, in Proceeding of IWAENC (2008)
12.
Y. Uemura, Y. Takahashi, H. Saruwatari, K. Shikano, K. Kondo, Musical noise generation analysis for noise reduction methods based on spectral subtraction and MMSE STSA estimation, in Proceeding of ICASSP (2009), pp. 4433–4436
13.
Y. Takahashi, R. Miyazaki, H. Saruwatari, K. Kondo, Theoretical analysis of musical noise in nonlinear noise reduction based on higher-order statistics, in Proceeding of APSIPA Annual Summit and Conference (2012)
14.
K. Yamashita, S. Ogata, T. Shimamura, Spectral subtraction iterated with weighting factors, in Proceeding of IEEE Speech Coding Workshop (2002), pp. 138–140
15.
M.R. Khan, T. Hansen, Iterative noise power subtraction technique for improved speech quality, in Proceeding of ICECE (2008), pp. 391–394
16.
S. Li, J.-Q. Wang, M. Niu, X.-J. Jing, T. Liu, Iterative spectral subtraction method for millimeter-wave conducted speech enhancement. J. Biomed. Sci. Eng. 2010(3), 187–192 (2010)CrossRef
17.
T. Inoue, H. Saruwatari, Y. Takahashi, K. Shikano, K. Kondo, Theoretical analysis of iterative weak spectral subtraction via higher-order statistics, in Proceeding of IEEE International Workshop on Machine Learning for Signal Processing (2010), pp. 220–225
18.
R. Miyazaki, H. Saruwatari, T. Inoue, Y. Takahashi, K. Shikano, K. Kondo, Musical-noise-free speech enhancement based on optimized iterative spectral subtraction. IEEE Trans. Audio Speech Lang. Process. 20(7), 2080–2094 (2012)CrossRef
19.
R. Miyazaki, H. Saruwatari, S. Nakamura, K. Shikano, K. Kondo, J. Blanchette, M. Bouchard, Musical-noise-free blind speech extraction integrating microphone array and iterative spectral subtraction. Signal Process. (Elsevier) 102, 226–239 (2014)CrossRef
20.
P. Comon, Independent component analysis, a new concept? Signal Process. (Elsevier) 36, 287–314 (1994)CrossRefMATH
21.
S. Araki, R. Mukai, S. Makino, T. Nishikawa, H. Saruwatari, The fundamental limitation of frequency domain blind source separation for convolutive mixtures of speech. IEEE Trans. Speech Audio Process. 11(2), 109–116 (2003)CrossRefMATH
22.
H. Sawada, R. Mukai, S. Araki, S. Makino, A robust and precise method for solving the permutation problem of frequency-domain blind source separation. IEEE Trans. Speech Audio Process. 12(5), 530–538 (2004)CrossRef
23.
H. Saruwatari, T. Kawamura, T. Nishikawa, A. Lee, K. Shikano, Blind source separation based on a fast-convergence algorithm combining ICA and beamforming. IEEE Trans. Audio Speech Lang. Process. 14(2), 666–678 (2006)CrossRef
24.
A. Homayoun, M. Bouchard, Improved noise power spectrum density estimation for binaural hearing aids operating in a diffuse noise field environment. IEEE Trans. Audio Speech Lang. Process. 17(4), 521–533 (2009)CrossRef
25.
T. Inoue, H. Saruwatari, Y. Takahashi, K. Shikano, K. Kondo, Theoretical analysis of musical noise in generalized spectral subtraction based on higher order statistics. IEEE Trans. Audio Speech Lang. Process. 19(6), 1770–1779 (2011)CrossRef
26.
H. Yu, T. Fingscheidt, A figure of merit for instrumental optimization of noise reduction algorithms, in Proceeding of DSP in Vehicles (2011)
27.
H. Yu, T. Fingscheidt, Black box measurement of musical tones produced by noise reduction systems, in Proceeding of ICASSP (2012), pp. 4573–4576
28.
S. Kanehara, H. Saruwatari, R. Miyazaki, K. Shikano, K. Kondo, Theoretical analysis of musical noise generation in noise reduction methods with decision-directed a priori SNR estimator, in Proceeding of IWAENC (2012)
29.
S. Kanehara, H. Saruwatari, R. Miyazaki, K. Shikano, K. Kondo, Comparative study on various noise reduction methods with decision-directed a priori SNR estimator via higher-order statistics, in Proceeding of APSIPA Annual Summit and Conference (2012)
30.
R. Miyazaki, H. Saruwatari, K. Shikano, K. Kondo, Musical-noise-free speech enhancement based on iterative Wiener filtering, in Proceeding of IEEE International Symposium on Signal Processing and Information Technology (2012)
31.
S. Nakai, H. Saruwatari, R. Miyazaki, S. Nakamura, K. Kondo, Theoretical analysis of biased MMSE short-time spectral amplitude estimator and its extension to musical-noise-free speech enhancement, in Proceeding of Hands-Free Speech Communication and Microphone Arrays (2014)
32.
H. Saruwatari, Statistical-model-based speech enhancement with musical-noise-free properties, in Proceeding of IEEE International Conference on Digital Signal Processing (2015), pp. 1201–1205
33.
A. Hiroe, Solution of permutation problem in frequency domain ICA using multivariate probability density functions, in Proceeding of ICA (2006), pp. 601–608
34.
T. Kim, H.T. Attias, S.-Y. Lee, T.-W. Lee, Blind source separation exploiting higher-order frequency dependencies. IEEE Trans. Audio Speech Lang. Process. 15(1), 70–79 (2007)CrossRef
35.
N. Ono, Stable and fast update rules for independent vector analysis based on auxiliary function technique, in Proceeding of WASPAA (2011), pp. 189–192
36.
D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, Relaxation of rank-1 spatial constraint in overdetermined blind source separation, in Proceeding of EUSIPCO (2015), pp. 1271–1275
37.
D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, Determined blind source separation unifying independent vector analysis and nonnegative matrix factorization. IEEE/ACM Trans. Audio Speech Lang. Process. 24(9), 1626–1641 (2016)CrossRef
38.
Y. Mitsui, D. Kitamura, S. Takamichi, N. Ono, H. Saruwatari, Blind source separation based on independent low-rank matrix analysis with sparse regularization for time-series activity, in Proceeding of ICASSP (2017), pp. 21–25
39.
S. Mogami, D. Kitamura, Y. Mitsui, N. Takamune, H. Saruwatari, N. Ono, Independent low-rank matrix analysis based on complex Student’s \(t\)-distribution for blind audio source separation, in Proceeding of IEEE International Workshop on Machine Learning for Signal Processing (2017)
40.
F.D. Aprilyanti, J. Even, H. Saruwatari, K. Shikano, S. Nakamura, T. Takatani, Suppression of noise and late reverberation based on blind signal extraction and Wiener filtering. Acoust. Sci. Technol. 36(4), 302–313 (2015)CrossRef
41.
H. Saruwatari, S. Kurita, K. Takeda, F. Itakura, T. Nishikawa, Blind source separation combining independent component analysis and beamforming. EURASIP J. Appl. Signal Process. 2003, 1135–1146 (2003)MATH
42.
Y. Takahashi, T. Takatani, K. Osako, H. Saruwatari, K. Shikano, Blind spatial subtraction array for speech enhancement in noisy environment. IEEE Trans. Audio Speech Lang. Process. 17(4), 650–664 (2009)CrossRef
43.
Y. Takahashi, H. Saruwatari, K. Shikano, K. Kondo, Musical-noise analysis in methods of integrating microphone array and spectral subtraction based on higher-order statistics. EURASIP J. Adv. Signal Process. 2010(431347), 25 pages (2010)
44.
H. Saruwatari, Y. Ishikawa, Y. Takahashi, T. Inoue, K. Shikano, K. Kondo, Musical noise controllable algorithm of channelwise spectral subtraction and adaptive beamforming based on higher-order statistics. IEEE Trans. Audio Speech Lang. Process. 19(6), 1457–1466 (2011)CrossRef
45.
R. Miyazaki, H. Saruwatari, K. Shikano, Theoretical analysis of amounts of musical noise and speech distortion in structure-generalized parametric spatial subtraction array. IEICE Trans. Fundam. 95-A(2), 586–590 (2012)
46.
S. Kurita, H. Saruwatari, S. Kajita, K. Takeda, F. Itakura, Evaluation of blind signal separation method using directivity pattern under reverberant conditions, in Proceeding of ICASSP, vol. 5 (2000), pp. 3140–3143
47.
J. Even, H. Saruwatari, K. Shikano, T. Takatani, Speech enhancement in presence of diffuse background noise: Why using blind signal extraction? in Proceeding of ICASSP (2010), pp. 4770–4773
48.
J. Even, C. Ishi, H. Saruwatari, N. Hagita, Close speaker cancellation for suppression of non-stationary background noise for hands-free speech interface, in Proceeding of INTERSPEECH (2010), pp. 977–980
49.
R. Prasad, H. Saruwatari, K. Shikano, Probability distribution of time-series of speech spectral components, IEICE Trans. Fundam. E87-A(3), 584–597 (2004)
50.
R. Prasad, H. Saruwatari, K. Shikano, Estimation of shape parameter of GGD function by negentropy matching. Neural Process. Lett. 22, 377–389 (2005)CrossRef
51.
T.H. Dat, K. Takeda, F. Itakura, Generalized gamma modeling of speech and its online estimation for speech enhancement, in Proceeding of ICASSP, vol. 4 (2005), pp. 181–184
52.
I. Andrianakis, P.R. White, MMSE speech spectral amplitude estimators with chi and gamma speech priors, in Proceeding of ICASSP (2006), pp. III-1068–III-1071
53.
R. Wakisaka, H. Saruwatari, K. Shikano, T. Takatani, Speech prior estimation for generalized minimum mean-square error short-time spectral amplitude estimator. IEICE Trans. Fundam. 95-A(2), 591–595 (2012)
54.
R. Wakisaka, H. Saruwatari, K. Shikano, T. Takatani, Speech kurtosis estimation from observed noisy signal based on generalized Gaussian distribution prior and additivity of cumulants, in Proceeding of ICASSP (2012), pp. 4049–4052
55.
I. Cohen, Optimal speech enhancement under signal presence uncertainty using log-spectra amplitude estimator. IEEE Signal Process. Lett. 9(4), 113–116 (2002)CrossRef
56.
H. Buchner, R. Aichner, W. Kellermann, A generalization of blind source separation algorithms for convolutive mixtures based on second-order statistics. IEEE Trans. Speech Audio Process. 13(1), 120–134 (2005)CrossRef
57.
Y. Mori, H. Saruwatari, T. Takatani, S. Ukai, K. Shikano, T. Hiekata, Y. Ikeda, H. Hashimoto, T. Morita, Blind separation of acoustic signals combining SIMO-model-based independent component analysis and binary masking. EURASIP J. Appl. Signal Process. 2006(34970), 17 pages (2006)
58.
T. Hiekata, Y. Ikeda, T. Yamashita, T. Morita, R. Zhang, Y. Mori, H. Saruwatari, K. Shikano, Development and evaluation of pocket-size real-time blind source separation microphone. Acoust. Sci. Technol. 30(4), 297–304 (2009)CrossRef
59.
Y. Omura, H. Kamado, H. Saruwatari, K. Shikano, Real-time semi-blind speech extraction with speaker direction tracking on Kinect, in Proceeding of APSIPA Annual Summit and Conference (2012)
60.
Y. Bando, H. Saruwatari, N. Ono, S. Makino, K. Itoyama, D. Kitamura, M. Ishimura, M. Takakusaki, N. Mae, K. Yamaoka, Y. Matsui, Y.i Ambe, M. Konyo, S. Tadokoro, K. Yoshii, H.G. Okuno, Low-latency and high-quality two-stage human-voice-enhancement system for a hose-shaped rescue robot. J. Robot. Mechatron. 29(1), 198–212 (2017)
Metadata
Title
Musical-Noise-Free Blind Speech Extraction Based on Higher-Order Statistics Analysis
Authors
Hiroshi Saruwatari
Ryoichi Miyazaki
Copyright Year
2018
Book
Audio Source Separation

Print ISBN: 978-3-319-73030-1

Electronic ISBN: 978-3-319-73031-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-73031-8_13