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

来源：

2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING | 2010年

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

页码：4430 / 4433

页数：4

共 50 条

[31] ANALYSIS OF ROBUSTNESS OF DEEP SINGLE-CHANNEL SPEECH SEPARATION USING CORPORA CONSTRUCTED FROM MULTIPLE DOMAINS
Maciejewski, Matthew
Sell, Gregory
Fujita, Yusuke
Garcia-Perera, Leibny Paola
Watanabe, Shinji
Khudanpur, Sanjeev
2019 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA), 2019, : 165 - 169
[32] Multi-Head Self-Attention-Based Deep Clustering for Single-Channel Speech Separation
Jin, Yanliang
Tang, Chenjun
Liu, Qianhong
Wang, Yan
IEEE ACCESS, 2020, 8 : 100013 - 100021
[33] Speech Separation with EMD as Front-End for Noise Robust Co-Channel Speaker Identification
Kumar, Prasanna M. K.
Kumaraswamy, R.
2016 INTERNATIONAL CONFERENCE ON CIRCUITS, CONTROLS, COMMUNICATIONS AND COMPUTING (I4C), 2016,
[34] Threshold-Based Combination of Ideal Binary Mask and Ideal Ratio Mask for Single-Channel Speech Separation
Chen, Peng
Nguyen, Binh Thien
Iwai, Kenta
Nishiura, Takanobu
INFORMATION, 2024, 15 (10)
[35] A MAP CRITERION FOR DETECTING THE NUMBER OF SPEAKERS AT FRAME LEVEL IN MODEL-BASED SINGLE-CHANNEL SPEECH SEPARATION
Mowlaee, P.
Christensen, M. G.
Tan, Z. -H.
Jensen, S. H.
2010 CONFERENCE RECORD OF THE FORTY FOURTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS (ASILOMAR), 2010, : 538 - 541
[36] Single-Channel Speech Separation Based on Non-negative Matrix Factorization and Factorial Conditional Random Field
Li Xu
Tu Ming
Wang Xiaofei
Wu Chao
Fu Qiang
Yan Yonghong
CHINESE JOURNAL OF ELECTRONICS, 2018, 27 (05) : 1063 - 1070
[37] Single-Channel Speech Separation Based on Non-negative Matrix Factorization and Factorial Conditional Random Field
LI Xu
TU Ming
WANG Xiaofei
WU Chao
FU Qiang
YAN Yonghong
Chinese Journal of Electronics, 2018, 27 (05) : 1063 - 1070
[38] SINUSOIDAL MASKS FOR SINGLE CHANNEL SPEECH SEPARATION
Mowlaee, Pejman
Christensen, Mads Graesboll
Jensen, Soren Holdt
2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, : 4262 - 4265
[39] Joint Speech Enhancement and Speaker Identification Using Monte Carlo Methods
Maina, Ciira Wa
Walsh, John MacLaren
INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5, 2009, : 1359 - 1362
[40] Joint Speech Enhancement and Speaker Identification Using Approximate Bayesian Inference
Maina, Ciira Wa
Walsh, John MacLaren
IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2011, 19 (06): : 1517 - 1529

← 1 2 3 4 5 →