A Robust Blind Source Separation Algorithm Based on Non-negative Matrix Factorization and Frequency-Sliding Generalized Cross-Correlation
- Resource Type
- Conference
- Authors
- Wang, Shiting; Zhou, Yi; Yang, Xiuxiang; Liu, Hongqing
- Source
- 2021 IEEE Statistical Signal Processing Workshop (SSP) Statistical Signal Processing Workshop (SSP), 2021 IEEE. :231-235 Jul, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Signal Processing and Analysis
Time-frequency analysis
Signal processing algorithms
Estimation
Frequency estimation
Blind source separation
Reverberation
Noise measurement
blind source separation
NMF
TDE
frequency-sliding
GCC
- Language
- ISSN
- 2693-3551
In this paper, a blind source separation algorithm based on time delay estimation (TDE) and non-negative matrix factorization (NMF) is proposed. In the TDE module, sub-band generalized cross correlation (GCC), frequency-sliding and singular value decomposition (SVD) techniques are used to get more accurate estimation. The time differences of arrival (TDOA) estimation of sources can be obtained from weighted low-rank approximation of the Frequency-Sliding GCC (FS-GCC) matrix. Then the sound sources are reconstructed in the NMF module by grouping the dictionary atoms according to their spatial information. The experiment uses utterances from SiSEC2018 database. Performance is quantified using the BSS Eval toolkits. Results prove that the proposed algorithm outperforms the compared ones in the noisy environments.