Low Latency Online Blind Source Separation Based on Joint Optimization with Blind Dereverberation
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- Tetsuya Ueda
- NTT Corporation,Japan
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- Tomohiro Nakatani
- NTT Corporation,Japan
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- Rintaro Ikeshita
- NTT Corporation,Japan
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- Keisuke Kinoshita
- NTT Corporation,Japan
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- Shoko Araki
- NTT Corporation,Japan
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- Shoji Makino
- University of Tsukuba,Japan
説明
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.
収録刊行物
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- ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 506-510, 2021-06-06
IEEE