抄録
This paper presents an online real-time method that enhances human voices included in severely noisy audio signals captured by microphones of a hose-shaped rescue robot. To help a remote operator of such a robot pick up a weak voice of a human buried under rubble, it is crucial to suppress the loud ego-noise caused by the movements of the robot in real time. We tackle this task by using online robust principal component analysis (ORPCA) for decomposing the spectrogram of an observed noisy signal into the sum of low-rank and sparse spectrograms that are expected to correspond to periodic ego-noise and human voices. Using a microphone array distributed on the long body of a hose-shaped robot, ego-noise suppression can be further improved by combining the results of ORPCA applied to the observed signal captured by each microphone. Experiments using a 3-m hose-shaped rescue robot with eight microphones show that the proposed method improves the performance of conventional ego-noise suppression using only one microphone by 7.4 dB in SDR and 17.2 in SIR.
| 元の言語 | English |
|---|---|
| ホスト出版物のタイトル | SSRR 2015 - 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics |
| 出版者 | Institute of Electrical and Electronics Engineers Inc. |
| ISBN（印刷物） | 9781509019595 |
| DOI | |
| 出版物ステータス | Published - 2016 3 29 |
| イベント | IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2015 - West Lafayette, United States 継続期間: 2015 10 18 → 2015 10 20 |
Other
| Other | IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2015 |
|---|---|
| 国 | United States |
| 市 | West Lafayette |
| 期間 | 15/10/18 → 15/10/20 |
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ASJC Scopus subject areas
- Artificial Intelligence
- Control and Systems Engineering
- Safety Research
これを引用
Human-voice enhancement based on online RPCA for a hose-shaped rescue robot with a microphone array. / Bando, Yoshiaki; Itoyama, Katsutoshi; Konyo, Masashi; Tadokoro, Satoshi; Nakadai, Kazuhiro; Yoshii, Kazuyoshi; Okuno, Hiroshi G.
SSRR 2015 - 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics. Institute of Electrical and Electronics Engineers Inc., 2016. 7442949.研究成果: Conference contribution
}
TY - GEN
T1 - Human-voice enhancement based on online RPCA for a hose-shaped rescue robot with a microphone array
AU - Bando, Yoshiaki
AU - Itoyama, Katsutoshi
AU - Konyo, Masashi
AU - Tadokoro, Satoshi
AU - Nakadai, Kazuhiro
AU - Yoshii, Kazuyoshi
AU - Okuno, Hiroshi G.
PY - 2016/3/29
Y1 - 2016/3/29
N2 - This paper presents an online real-time method that enhances human voices included in severely noisy audio signals captured by microphones of a hose-shaped rescue robot. To help a remote operator of such a robot pick up a weak voice of a human buried under rubble, it is crucial to suppress the loud ego-noise caused by the movements of the robot in real time. We tackle this task by using online robust principal component analysis (ORPCA) for decomposing the spectrogram of an observed noisy signal into the sum of low-rank and sparse spectrograms that are expected to correspond to periodic ego-noise and human voices. Using a microphone array distributed on the long body of a hose-shaped robot, ego-noise suppression can be further improved by combining the results of ORPCA applied to the observed signal captured by each microphone. Experiments using a 3-m hose-shaped rescue robot with eight microphones show that the proposed method improves the performance of conventional ego-noise suppression using only one microphone by 7.4 dB in SDR and 17.2 in SIR.
AB - This paper presents an online real-time method that enhances human voices included in severely noisy audio signals captured by microphones of a hose-shaped rescue robot. To help a remote operator of such a robot pick up a weak voice of a human buried under rubble, it is crucial to suppress the loud ego-noise caused by the movements of the robot in real time. We tackle this task by using online robust principal component analysis (ORPCA) for decomposing the spectrogram of an observed noisy signal into the sum of low-rank and sparse spectrograms that are expected to correspond to periodic ego-noise and human voices. Using a microphone array distributed on the long body of a hose-shaped robot, ego-noise suppression can be further improved by combining the results of ORPCA applied to the observed signal captured by each microphone. Experiments using a 3-m hose-shaped rescue robot with eight microphones show that the proposed method improves the performance of conventional ego-noise suppression using only one microphone by 7.4 dB in SDR and 17.2 in SIR.
UR - http://www.scopus.com/inward/record.url?scp=84966783460&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84966783460&partnerID=8YFLogxK
U2 - 10.1109/SSRR.2015.7442949
DO - 10.1109/SSRR.2015.7442949
M3 - Conference contribution
AN - SCOPUS:84966783460
SN - 9781509019595
BT - SSRR 2015 - 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics
PB - Institute of Electrical and Electronics Engineers Inc.
ER -