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May 2017

多チャンネル低ランク・スパース分解に基づく柔軟索状レスキューロボットのためのリアルタイム音声強調

  • 坂東宜昭, 安部祐一, 糸山克寿, 昆陽雅司, 田所諭, 中臺一博, 吉井和佳, 奥乃博,
  • in ロボティクス・メカトロニクス 講演会2017 講演論文集,
  • 日本機械学会,
  • 2017,
  • Conference paper

This paper presents a real-time human-voice enhancement method for a hose-shaped rescue robot based on multi-channel low-rank sparse decomposition. Although microphone arrays equipped on hose-shaped robots are crucial for finding victims under collapsed buildings, human voices captured by the microphone array are contaminated by environment-dependent and nonstationary ego-noise. Our method decomposes multi-channel amplitude spectrograms into sparse and low-rank components (human voice and noise) without any prior training. This decomposition is conducted with a state-space model representing the dynamics of these components in a mini-batch manner. Experimental results show that the performance difference between our method and its offline version is less than 3 dB in signal-to-distortion ratio.

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