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Blind Source Separation Using dodecahedral microphone array under Reverberant Conditions

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2011年第3期E94A卷 897-906页

作者： Ogasawara, Motoki Nishino, Takanori Takeda, Kazuya Nagoya Univ Grad Sch Informat Sci Nagoya Aichi 4648603 Japan Mie Univ Grad Sch Engn Tsu Mie 5148507 Japan

The separation and localization of sound source signals are important techniques for many applications, such as highly realistic communication and speech recognition systems. These systems are expected to work without such prior information as the number of sound sources and the environmental conditions. In this paper, we developed a dodecahedral microphone array and proposed a novel separation method with our developed device. This method refers to human sound localization cues and uses acoustical characteristics obtained by the shape of the dodecahedral microphone array. Moreover, this method includes an estimation method of the number of sound sources that can operate without prior information. The sound source separation performances were evaluated under simulated and actual reverberant conditions, and the results were compared with the conventional method. The experimental results showed that our separation performance outperformed the conventional method.

关键词： dodecahedral microphone array frequency domain independent component analysis (FD-ICA) signal-to-intetference ratio improvement score

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Effective Frame Selection for Blind Source Separation Based on Frequency Domain Independent Component Analysis

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2014年第3期E97A卷 784-791页

作者： Mizuno, Yusuke Kondo, Kazunobu Nishino, Takanori Kitaoka, Norihide Takeda, Kazuya Nagoya Univ Grad Sch Informat Sci Nagoya Aichi 4648603 Japan Yamaha Corp Ctr Corp Res & Dev Iwata 4380192 Japan Mie Univ Grad Sch Engn Tsu Mie 5148507 Japan

Blind source separation is a technique that can separate sound sources without such information as source location, the number of sources, and the utterance content. Multi-channel source separation using many microphones separates signals with high accuracy, even if there are many sources. However, these methods have extremely high computational complexity, which must be reduced. In this paper, we propose a computational complexity reduction method for blind source separation based on frequency domain independent component analysis (FDICA) and examine temporal data that are effective for source separation. A frame with many sound sources is effective for FDICA source separation. We assume that a frame with a low kurtosis has many sound sources and preferentially select such frames. In our proposed method, we used the log power spectrum and the kurtosis of the magnitude distribution of the observed data as selection criteria and conducted source separation experiments using speech signals from twelve speakers. We evaluated the separation performances by the signal-to-interference ratio (SIR) improvement score. From our results, the SIR improvement score was 24.3 dB when all the frames were used, and 23.3 dB when the 300 frames selected by our criteria were used. These results clarified that our proposed selection criteria based on kurtosis and magnitude is effective. Furthermore, we significantly reduced the computational complexity because it is proportional to the number of selected frames.

关键词： dodecahedral microphone array frequency domain independent component analysis computational complexity reduction signal to interference ratio improvement

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FAST SOURCE SEPARATION BASED ON SELECTION OF EFFECTIVE TEMPORAL FRAMES

FAST SOURCE SEPARATION BASED ON SELECTION OF EFFECTIVE TEMPO...

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20th European Signal Processing Conference (EUSIPCO)

作者： Mizuno, Yusuke Kondo, Kazunobu Nishino, Takanori Kitaoka, Norihide Takeda, Kazuya Nagoya Univ Grad Sch Informat Sci Nagoya Aichi 4648603 Japan Yamaha Corp Corp Res & Dev Ctr Shizuoka 4380192 Japan Mie Univ Grad Sch Engn Tsu Mie 5148507 Japan

ISBN: (纸本)9781467310680

A faster computational method for performing frequency domain independent component analysis (FDICA) using a dodecahedral microphone array is proposed. Source separation with FDICA uses the spectrum of observed signals and estimates separation filters for each frequency. However, this technique is complex and requires high computational resources. In this paper, a method of selecting temporal frames which are effective for training the separation filters is proposed and evaluated. The log power spectrum and the kurtosis of amplitude distribution are employed as selection criteria. Performance was evaluated by comparing signal-to-interference performance with that of the conventional method. Experimental results showed that the proposed method reduced computation to 17.1 % of that required by the conventional method, and that separation performance of the proposed method is superior. Therefore, the proposed method can achieve faster computation with lower computational complexity, and its effectiveness can be confirmed.

关键词： dodecahedral microphone array Frequency domain independent component analysis Computational complexity reduction Signal-to-interference improvement

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