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Title: Source Adaptive Blind Signal Extraction Using Closed-Form ICA for Hands-Free Robot Spoken Dialogue System
Authors: Yu Takahashi
Hiroshi Saruwatari
Yuki Fujihara
Kentaro Tachibana
Yoshimitsu Mori
Shigeki Miyabe
Kiyohiro Shikano
Akira Tanaka
Keywords: Separation
speech enhancement
acoustic signal processing
adaptive signal processing
Issue Date: Apr-2009
Publisher: IEEE
Start page: 3681
End page: 3684
Abstract: In this paper, we propose a new ICA-based BSS algorithm including estimation of sources' probability density functions (PDFs) to adapt the nonlinear activation function to various noise conditions. In the proposed method, closed-form second-order ICA is introduced as a computational-cost-efficient preprocessing to extract sources' PDFs, which is beneficial for real-time application. Compared with various type of conventional ICAs, e.g., fixed activation-function type and ML-based type, our proposed algorithm can give a faster and higher convergence. Based on the proposed source-adaptive ICA, we show a real-time noise reduction results under diffuse noise environment. Also we can demonstrate our recently developed hands-free robot spoken dialogue system via real-time ICA.
Description: ICASSP2009: IEEE International Conference on Acoustics, Speech, and Signal Processing, April 19-24, 2009, Taipei, Taiwan.
ISBN: 9781424423545
ISSN: 1520-6149
Rights: Copyright 2009 IEEE
Text Version: Publisher
Publisher DOI: 10.1109/ICASSP.2009.4960425
Appears in Collections:情報科学研究科 / Graduate School of Information Science

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