Abstract
This paper presents a new low-latency online blind source separation (BSS) algorithm. Although algorithmic delay of a frequency domain online BSS can be reduced simply by shortening the short-time Fourier transform (STFT) frame length, it degrades the source separation performance in the presence of reverberation. This paper proposes a method to solve this problem by integrating BSS with Weighted Prediction Error (WPE) based dereverberation. Although a simple cascade of online BSS after online WPE upgrades the separation performance, the overall optimality is not guaranteed. Instead, this paper extends a recently proposed batch processing algorithm that can jointly optimize dereverberation and separation so that it can perform online processing with low computational cost and little processing delay (< 12 ms). The results of a source separation experiment in a noisy car environment suggest that the proposed online method has better separation performance than the simple cascaded methods.
Original language | English |
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Pages (from-to) | 506-510 |
Number of pages | 5 |
Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Volume | 2021-June |
DOIs | |
Publication status | Published - 2021 |
Externally published | Yes |
Event | 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Virtual, Toronto, Canada Duration: 2021 Jun 6 → 2021 Jun 11 |
Keywords
- Blind dereverberation
- Blind source separation
- Independent vector analysis
- Online
- Real-time
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering