JOINT SINGLE-CHANNEL SPEECH SEPARATION AND SPEAKER IDENTIFICATION

被引:13
|
作者
Mowlaee, P. [1 ]
Saeidi, R. [2 ]
Tan, Z. -H. [1 ]
Christensen, M. G. [3 ]
Franti, P. [2 ]
Jensen, S. H. [1 ]
机构
[1] Aalborg Univ, Dept Elect Syst, Aalborg, Denmark
[2] Univ Joensuu, Dept Comp Sci & Stat, Joensuu, Finland
[3] Aalborg Univ, Dept Media, Aalborg, Denmark
关键词
Single-channel speech separation; speaker identification; sinusoidal mixture estimator; vector quantization; Gaussian mixture model;
D O I
10.1109/ICASSP.2010.5495619
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
In this paper, we propose a closed loop system to improve the performance of single-channel speech separation in a speaker independent scenario. The system is composed of two interconnected blocks: a separation block and a speaker identification block. The improvement is accomplished by incorporating the speaker identities found by the speaker identification block as additional information for the separation block, which converts the speaker-independent separation problem to a speaker-dependent one where the speaker codebooks are known. Simulation results show that the closed loop system enhances the quality of the separated output signals. To assess the improvements, the results are reported in terms of PESQ for both target and masked signals.
引用
下载
收藏
页码:4430 / 4433
页数:4
相关论文
共 50 条
  • [21] A Speaker-Dependent Approach to Single-Channel Joint Speech Separation and Acoustic Modeling Based on Deep Neural Networks for Robust Recognition of Multi-Talker Speech
    Tu, Yan-Hui
    Du, Jun
    Lee, Chin-Hui
    JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2018, 90 (07): : 963 - 973
  • [22] A Speaker-Dependent Approach to Single-Channel Joint Speech Separation and Acoustic Modeling Based on Deep Neural Networks for Robust Recognition of Multi-Talker Speech
    Yan-Hui Tu
    Jun Du
    Chin-Hui Lee
    Journal of Signal Processing Systems, 2018, 90 : 963 - 973
  • [23] Deep Clustering in Complex Domain for Single-Channel Speech Separation
    Liu, Runling
    Tang, Yu
    Mang, Hongwei
    2022 IEEE 17TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2022, : 1463 - 1468
  • [24] IMPROVED SINGLE-CHANNEL SPEECH SEPARATION USING SINUSOIDAL MODELING
    Mowlaee, Pejman
    Christensen, Mads Graesboll
    Jensen, Soren Holdt
    2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, : 21 - 24
  • [25] Single-channel Speech Separation based on Gaussian Process Regression
    Le Dinh Nguyen
    Chen, Sih-Huei
    Tai, Tzu-Chiang
    Wang, Jia-Ching
    2018 IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA (ISM 2018), 2018, : 275 - 278
  • [26] A PITCH-AWARE APPROACH TO SINGLE-CHANNEL SPEECH SEPARATION
    Wang, Ke
    Soong, Frank
    Xie, Lei
    2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2019, : 296 - 300
  • [27] Phase estimation for signal reconstruction in single-channel speech separation
    Mowlaee, Pejman
    Saeidi, Rahim
    Martin, Rainer
    13TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2012 (INTERSPEECH 2012), VOLS 1-3, 2012, : 1546 - 1549
  • [28] Linear regression on sparse features for single-channel speech separation
    Schmidt, Mikkel N.
    Olsson, Rasmus K.
    2007 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS, 2007, : 149 - 152
  • [29] Single-channel speech separation using soft mask filtering
    Radfar, Mohammad H.
    Dansereau, Richard M.
    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2007, 15 (08): : 2299 - 2310
  • [30] Sinusoidal Approach for the Single-Channel Speech Separation and Recognition Challenge
    Mowlaee, P.
    Saeidi, R.
    Tan, Z. -H.
    Christensen, M. G.
    Kinnunen, T.
    Franti, P.
    Jensen, S. H.
    12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5, 2011, : 684 - +