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Ego Noise Reduction for Hose-Shaped Rescue Robot Combining Independent Low-Rank Matrix Analysis and Multichannel Noise Cancellation

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Book cover Latent Variable Analysis and Signal Separation (LVA/ICA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10169))

Abstract

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.

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Acknowledgments

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.

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Authors and Affiliations

  1. University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8573, Japan

    Narumi Mae, Masaru Ishimura, Shoji Makino & Takeshi Yamada

  2. SOKENDAI (The Graduate University for Advanced Studies), Shonan Village, Hayama, Kanagawa, 240-0193, Japan

    Daichi Kitamura & Nobutaka Ono

  3. National Institute of Informatics (NII), 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, 101-8430, Japan

    Nobutaka Ono

  4. The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8654, Japan

    Hiroshi Saruwatari

Authors
  1. Narumi Mae
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  2. Masaru Ishimura
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  3. Shoji Makino
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  4. Daichi Kitamura
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  5. Nobutaka Ono
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  6. Takeshi Yamada
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  7. Hiroshi Saruwatari
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Corresponding author

Correspondence to Narumi Mae .

Editor information

Editors and Affiliations

  1. Institute of Information Theory and Automation, Prague, Czech Republic

    Petr Tichavský

  2. Sharif University of Technology, Tehran, Iran

    Massoud Babaie-Zadeh

  3. Grenoble-Alpes University, Grenoble, France

    Olivier J.J. Michel

  4. Toulon University, Toulon, France

    Nadège Thirion-Moreau

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Mae, N. et al. (2017). Ego Noise Reduction for Hose-Shaped Rescue Robot Combining Independent Low-Rank Matrix Analysis and Multichannel Noise Cancellation. In: Tichavský, P., Babaie-Zadeh, M., Michel, O., Thirion-Moreau, N. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2017. Lecture Notes in Computer Science(), vol 10169. Springer, Cham. https://doi.org/10.1007/978-3-319-53547-0_14

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  • DOI: https://doi.org/10.1007/978-3-319-53547-0_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53546-3

  • Online ISBN: 978-3-319-53547-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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