Paper ID | AUD-18.4 | ||
Paper Title | LOW LATENCY ONLINE BLIND SOURCE SEPARATION BASED ON JOINT OPTIMIZATION WITH BLIND DEREVERBERATION | ||
Authors | Tetsuya Ueda, University of Tsukuba, Japan; Tomohiro Nakatani, Rintaro Ikeshita, Keisuke Kinoshita, Shoko Araki, NTT Corporation, Japan; Shoji Makino, University of Tsukuba, Japan | ||
Session | AUD-18: Audio and Speech Source Separation 5: Source Separation | ||
Location | Gather.Town | ||
Session Time: | Thursday, 10 June, 13:00 - 13:45 | ||
Presentation Time: | Thursday, 10 June, 13:00 - 13:45 | ||
Presentation | Poster | ||
Topic | Audio and Acoustic Signal Processing: [AUD-SEP] Audio and Speech Source Separation | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
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. |