DIVERGENCE OPTIMIZATION IN NONNEGATIVE MATRIX FACTORIZATION WITH SPECTROGRAM RESTORATION FOR MULTICHANNEL SIGNAL SEPARATION

被引：0

作者：

Kitamura, Daichi ^{[1
]}

Saruwatari, Hiroshi ^{[1
]}

Nakamura, Satoshi ^{[1
]}

Takahashi, Yu ^{[2
]}

Kondo, Kazunobu ^{[2
]}

Kameoka, Hirokazu ^{[3
]}

机构：

[1] Nara Inst Sci & Technol, Nara 6300101, Japan

[2] Yamaha Corp, Shizuoka, Japan

[3] Univ Tokyo, Tokyo, Japan

来源：

2014 4TH JOINT WORKSHOP ON HANDS-FREE SPEECH COMMUNICATION AND MICROPHONE ARRAYS (HSCMA) | 2014年

关键词：

NMF; multichannel signal separation; music signal processing; spectrogram restoration; optimal divergence; AUDIO SOURCE SEPARATION; MIXTURES;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

In this paper, we address an optimization issue for the divergence in supervised nonnegative matrix factorization with spectrogram restoration, which has been proposed for addressing multichannel signal separation. This method separates non-target components and reconstructs some missing data caused by preceding spatial clustering via supervised basis extrapolation. In our previous study, we only used a limited type of divergence, whereas the divergence selection is essential. Therefore, we extend this method to a more generalized form and give a theoretical analysis of the divergence optimization, where we reveal the trade-off between separation and extrapolation abilities.

引用

页码：92 / 96

页数：5

共 50 条

[1] Multichannel Signal Separation Combining Directional Clustering and Nonnegative Matrix Factorization with Spectrogram Restoration
Kitamura, Daichi
Saruwatari, Hiroshi
Kameoka, Hirokazu
Takahashi, Yu
Kondo, Kazunobu
Nakamura, Satoshi
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2015, 23 (04) : 654 - 669
[2] Hybrid Multichannel Signal Separation Using Supervised Nonnegative Matrix Factorization with Spectrogram Restoration
Kitamura, Daichi
Saruwatari, Hiroshi
Nakamura, Satoshi
Takahashi, Yu
Kondo, Kazunobu
Kameoka, Hirokazu
2014 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA), 2014,
[3] BAYESIAN MULTICHANNEL NONNEGATIVE MATRIX FACTORIZATION FOR AUDIO SOURCE SEPARATION AND LOCALIZATION
Itakura, Kousuke
Bando, Yoshiaki
Nakamura, Eita
Itoyama, Katsutoshi
Yoshii, Kazuyoshi
Kawahara, Tatsuya
2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2017, : 551 - 555
[4] Multichannel Nonnegative Matrix Factorization in Convolutive Mixtures for Audio Source Separation
Ozerov, Alexey
Fevotte, Cedric
IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2010, 18 (03): : 550 - 563
[5] Sequential Initialization of Multichannel Nonnegative Matrix Factorization for Sound Source Separation
Uramoto, Takanobu
Tachioka, Yuuki
Narita, Tomohiro
Miura, Iori
Uenohara, Shingo
Furuya, Ken'ichi
2017 IEEE 6TH GLOBAL CONFERENCE ON CONSUMER ELECTRONICS (GCCE), 2017,
[6] Music Signal Separation Based on Supervised Nonnegative Matrix Factorization with Orthogonality and Maximum-Divergence Penalties
Kitamura, Daichi
Saruwatari, Hiroshi
Yagi, Kosuke
Shikano, Kiyohiro
Takahashi, Yu
Kondo, Kazunobu
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2014, E97A (05): : 1113 - 1118
[7] Projective Nonnegative Matrix Factorization with α-Divergence
Yang, Zhirong
Oja, Erkki
ARTIFICIAL NEURAL NETWORKS - ICANN 2009, PT I, 2009, 5768 : 20 - 29
[8] Algorithms for Nonnegative Matrix Factorization with the β-Divergence
Fevotte, Cedric
Idier, Jerome
NEURAL COMPUTATION, 2011, 23 (09) : 2421 - 2456
[9] On-line Nonnegative Matrix Factorization for Music Signal Separation
Lee, Seokjin
2014 TENTH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING (IIH-MSP 2014), 2014, : 566 - 569
[10] SPARSENESS-BASED MULTICHANNEL NONNEGATIVE MATRIX FACTORIZATION FOR BLIND SOURCE SEPARATION
Higuchi, Takuya
Yoshioka, Takuya
Nakatani, Tomohiro
2016 IEEE INTERNATIONAL WORKSHOP ON ACOUSTIC SIGNAL ENHANCEMENT (IWAENC), 2016,

← 1 2 3 4 5 →