TY - GEN
T1 - Ego noise reduction for hose-shaped rescue robot combining independent low-rank matrix analysis and multichannel noise cancellation
AU - Mae, Narumi
AU - Ishimura, Masaru
AU - Makino, Shoji
AU - Kitamura, Daichi
AU - Ono, Nobutaka
AU - Yamada, Takeshi
AU - Saruwatari, Hiroshi
N1 - Funding Information:
This work was supported by the Japan Science and Technology Agency and the Impulsing Paradigm Change through Disruptive Technologies Program (ImPACT) designed by the Council for Science, Technology and Innovation, and partly supported by SECOM Science and Technology Foundation. We would also like to express our gratitude to Prof. Hiroshi Okuno and Mr. Yoshiaki Bando for providing experimental data.
Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - In this paper, we present an ego noise reduction method for a hose-shaped rescue robot, developed for search and rescue operations in large-scale disasters. It is used to search for victims in disaster sites by capturing their voices with its microphone array. However, ego noises are mixed with voices, and it is difficult to differentiate them from a call for help from a disaster victim. To solve this problem, we here propose a two-step noise reduction method involving the following: (1) the estimation of both speech and ego noise signals from observed multichannel signals by multichannel nonnegative matrix factorization (NMF) with the rank-1 spatial constraint, and (2) the application of multichannel noise cancellation to the estimated speech signal using reference signals. Our evaluations show that this approach is effective for suppressing ego noise.
AB - In this paper, we present an ego noise reduction method for a hose-shaped rescue robot, developed for search and rescue operations in large-scale disasters. It is used to search for victims in disaster sites by capturing their voices with its microphone array. However, ego noises are mixed with voices, and it is difficult to differentiate them from a call for help from a disaster victim. To solve this problem, we here propose a two-step noise reduction method involving the following: (1) the estimation of both speech and ego noise signals from observed multichannel signals by multichannel nonnegative matrix factorization (NMF) with the rank-1 spatial constraint, and (2) the application of multichannel noise cancellation to the estimated speech signal using reference signals. Our evaluations show that this approach is effective for suppressing ego noise.
KW - Environment
KW - Independent vector analysis
KW - Multichannel noise cancellation
KW - Noise reduction
KW - Nonnegative matrix factorization
KW - Rescue robot
KW - Tough
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U2 - 10.1007/978-3-319-53547-0_14
DO - 10.1007/978-3-319-53547-0_14
M3 - Conference contribution
AN - SCOPUS:85013467024
SN - 9783319535463
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 141
EP - 151
BT - Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings
A2 - Tichavsky, Petr
A2 - Babaie-Zadeh, Massoud
A2 - Michel, Olivier J.J.
A2 - Thirion-Moreau, Nadege
PB - Springer Verlag
T2 - 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017
Y2 - 21 February 2017 through 23 February 2017
ER -