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Calibration of a Microphone Array Based on a Probabilistic Model of Microphone Positions

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Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices (IEA/AIE 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12144))

Abstract

This paper addresses a novel method for calibrating microphone positions included in a microphone array. The performance of microphone array processing deteriorates due to two factors: (1) differences between predetermined position and actual positions of the microphones. (2) sound source signal overlaps in frequency and time. To solve these problems, we propose a probabilistic generative model of the sound propagation process determined by microphone and sound source positions. The model is defined as the product of three probabilities: (1) prior probability of the microphone positions based on reference positions, (2) prior probability of the sound source spectrum, and (3) conditional probability of the recorded spectrum. Based on the model, an iterative algorithm to calibrate the microphone positions is derived as a solution of the maximum a posteriori estimation. Preliminary experiments through numerical simulation with an 8-ch microphone array revealed that the proposed method accurately estimated the microphone positions when using multiple sound sources. Preliminary experiments through numerical simulation with an 8-ch microphone array suggested the proposed method accurately estimated the microphone positions when using multiple sound sources.

This work was supported by JSPS KAKENHI Grant No. 16H02884, 17K00365, and 19K12017.

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Notes

  1. 1.

    Strictly, \(\textit{\textbf{S}}\) should be marginalized and the MAP estimation of \(p(\textit{\textbf{X}} | \textit{\textbf{Z}})\) should be solved.

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Authors and Affiliations

  1. School of Engineering, Tokyo Institute of Technology, 2-12-1, O-okayama, Meguro, Tokyo, 152-8552, Japan

    Katsuhiro Dan, Katsutoshi Itoyama, Kenji Nishida & Kazuhiro Nakadai

  2. Honda Research Insititute Japan Co., Ltd., 8-1 Honcho, Wako, Saitama, 351-0114, Japan

    Kazuhiro Nakadai

Authors
  1. Katsuhiro Dan
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  2. Katsutoshi Itoyama
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  3. Kenji Nishida
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  4. Kazuhiro Nakadai
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Corresponding author

Correspondence to Katsuhiro Dan .

Editor information

Editors and Affiliations

  1. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  2. Harbin Institute of Technology (Shenzhen), Shenzhen, China

    Philippe Fournier-Viger

  3. Texas State University, San Marcos, TX, USA

    Moonis Ali

  4. Iwate Prefectural University, Takizawa, Japan

    Jun Sasaki

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Dan, K., Itoyama, K., Nishida, K., Nakadai, K. (2020). Calibration of a Microphone Array Based on a Probabilistic Model of Microphone Positions. In: Fujita, H., Fournier-Viger, P., Ali, M., Sasaki, J. (eds) Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices. IEA/AIE 2020. Lecture Notes in Computer Science(), vol 12144. Springer, Cham. https://doi.org/10.1007/978-3-030-55789-8_53

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  • DOI: https://doi.org/10.1007/978-3-030-55789-8_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-55788-1

  • Online ISBN: 978-3-030-55789-8

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