An Approach to Solving a Permutation Problem of Frequency Domain Independent Component Analysis for Blind Source Separation of Speech Signals

被引:0
作者
Fujieda, Masaru [1 ]
Murakami, Takahiro [1 ]
Ishida, Yoshihisa [1 ]
机构
[1] Meiji Univ, Sch Sci & Technol, Kanagawa, Japan
来源
PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 18 | 2006年 / 18卷
关键词
Blind source separation; Independent component analysis; Frequency domain; Permutation ambiguity;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Independent component analysis (ICA) in the frequency domain is used for solving the problem of blind source separation (BSS). However, this method has some problems. For example, a general ICA algorithm cannot determine the permutation of signals which is important in the frequency domain ICA. In this paper, we propose an approach to the solution for a permutation problem. The idea is to effectively combine two conventional approaches. This approach improves the signal separation performance by exploiting features of the conventional approaches. We show the simulation results using artificial data.
引用
收藏
页码:64 / 68
页数:5
相关论文
共 50 条
  • [21] Nonparametric Bayesian sparse factor analysis for frequency domain blind source separation without permutation ambiguity
    Kohei Nagira
    Takuma Otsuka
    Hiroshi G Okuno
    EURASIP Journal on Audio, Speech, and Music Processing, 2013
  • [22] Blind source separation combining independent component analysis and beamforming
    Saruwatari, H
    Kurita, S
    Takeda, K
    Itakura, F
    Nishikawa, T
    Shikano, K
    EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING, 2003, 2003 (11) : 1135 - 1146
  • [23] Blind Source Separation Combining Independent Component Analysis and Beamforming
    Hiroshi Saruwatari
    Satoshi Kurita
    Kazuya Takeda
    Fumitada Itakura
    Tsuyoki Nishikawa
    Kiyohiro Shikano
    EURASIP Journal on Advances in Signal Processing, 2003
  • [24] Sparse Independent Component Analysis with Interpolation for Blind Source Separation
    Khan, Asif
    Kim, Intaek
    2009 2ND INTERNATIONAL CONFERENCE ON COMPUTER, CONTROL AND COMMUNICATION, 2009, : 29 - 34
  • [25] Improvements of blind source separation by using Independent Component Analysis
    Kataoka, Hidetoshi
    Nagasaka, Kenji
    WMSCI 2007: 11TH WORLD MULTI-CONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL II, PROCEEDINGS, 2007, : 165 - +
  • [26] Hybrid Source Prior Based Independent Vector Analysis for Blind Separation of Speech Signals
    Khan, Junaid Bahadar
    Jan, Tariqullah
    Khalil, Ruhul Amin
    Altalbe, Ali
    IEEE ACCESS, 2020, 8 : 132871 - 132881
  • [27] Sparse Kernel Independent Component Analysis for Blind Source Separation
    Khan, Asif
    Kim, Intaek
    JOURNAL OF THE OPTICAL SOCIETY OF KOREA, 2008, 12 (03) : 121 - 125
  • [28] STEREO SOURCE SEPARATION IN THE FREQUENCY DOMAIN: SOLVING THE PERMUTATION PROBLEM BY A SLIDING K-MEANS METHOD
    Chen, Bang-Yin
    Liu, Tzu-Chi
    Liu, Yi-Wen
    2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2019, : 4250 - 4254
  • [29] Blind source separation in frequency domain
    Zhou, Y
    Xu, BL
    SIGNAL PROCESSING, 2003, 83 (09) : 2037 - 2046
  • [30] A Blind Separation of Variable Speed Frequency Hopping Signals based on Independent Component Analysis
    Wang Miao
    Cai Xiao-xia
    Zhu Ke-fan
    PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019), 2019, : 144 - 148