| Paper: | MLSP-P5.10 | ||
| Session: | Blind Source Separation III | ||
| Time: | Friday, May 19, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Machine Learning for Signal Processing: Blind Signal Separation and Independent Component Analysis | ||
| Title: | FAST NOISE COMPENSATION FOR SPEECH SEPARATION IN DIFFUSE NOISE | ||
| Authors: | Rong Hu, Yunxin Zhao, University of Missouri-Columbia, United States | ||
| Abstract: | In this paper, a fast noise compensation (FNC) algorithm is proposed for the adaptive decorrelation filtering (ADF)speech separation system in the presence of diffuse noise. The adaptation of ADF is a dynamic process, making noise effects at ADF outputs time-varying in nature. Such changing noise effects need to be tracked and adaptively removed. Under the assumption that acoustic paths are slow in change and utilizing the filtering structure of the separation model, noise compensation terms were adapted with an FFT-based fast algorithm. Experiments were based on both simulated and real recorded diffuse noises. Strong diffuse noise distracts part of the attention of ADF to do noise cancellation while separating speech, and FNC works by forcing ADF to stay focused on speech separation task. The proposed algorithm significantly improved the separation performance of ADF system in diffuse noise. | ||
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