【学術・技術論文】

独立成分分析に基づく適応フィルタのロボット聴覚への適用

武田 龍・中臺 一博・駒谷 和範・尾形 哲也・奥乃 博

Robot Audition using an Adaptive Filter Based on Independent Component Analysis

Ryu Takeda・Kazuhiro Nakadai・Kazunori Komatani・Tetsuya Ogata・Hiroshi G. Okuno

This paper describes a new adaptive filter algorithm based on independent component analysis (ICA) for enhancing a target sound and for suppressing other interference sounds that are known. The technique can provide barge-in capable robot audition systems by utilizing known sound source signals such as self speech. Unlike a conventional ICA-based method, we use the time-frequency domain convolution model to cope with reflections of the sound. Experimental results showed that our method outperformed the conventional ICA-based method and the well-known adaptive filter algorithm called Nomalized Least Mean Squares (LMS). }

Key Words: Robot Audition・ Independent Component Analysis・ Adaptive Filtering・ Barge-In・ Multirate System

 [JRSJ Vol.26, No.6, pp.61-68]