Sound source separation using null-beamforming and spectral subtraction for mobile devices

Shintaro Takada; Satoshi Kanba; Tetsuji Ogawa; Kenzo Akagiri; Tetsunori Kobayashi

doi:10.1109/ASPAA.2007.4393006

Sound source separation using null-beamforming and spectral subtraction for mobile devices

Shintaro Takada^*, Satoshi Kanba, Tetsuji Ogawa, Kenzo Akagiri, Tetsunori Kobayashi

^*Corresponding author for this work

School of Fundamental Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Citations (Scopus)

Abstract

This paper presents a new type of speech segregation method for mobile devices in noisy sound situation, where two or more speakers are talking simultaneously. The proposed method consists of multiple null-beamformers, their minimum power channel selection and spectral subtraction. The proposed method is performed with space-saving and coplanar microphone arrangements and low-cost calculations, which are the very important requirements for the mobile application. Effectiveness of the proposed method is clarified in the segregation and the recognition experiments of two simultaneous continuous speeches: the method improved the PESQ-based MOS value by about one point and reduced 70% of word recognition errors compared with non-processing.

Original language	English
Title of host publication	2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA
Pages	30-33
Number of pages	4
DOIs	https://doi.org/10.1109/ASPAA.2007.4393006
Publication status	Published - 2007 Dec 1
Event	2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA - New Paltz, NY, United States Duration: 2007 Oct 21 → 2007 Oct 24

Publication series

Name	IEEE Workshop on Applications of Signal Processing to Audio and Acoustics

Conference

Conference	2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA
Country/Territory	United States
City	New Paltz, NY
Period	07/10/21 → 07/10/24

ASJC Scopus subject areas

Signal Processing

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10.1109/ASPAA.2007.4393006

Cite this

Takada, S., Kanba, S., Ogawa, T., Akagiri, K., & Kobayashi, T. (2007). Sound source separation using null-beamforming and spectral subtraction for mobile devices. In 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA (pp. 30-33). Article 4393006 (IEEE Workshop on Applications of Signal Processing to Audio and Acoustics). https://doi.org/10.1109/ASPAA.2007.4393006

Sound source separation using null-beamforming and spectral subtraction for mobile devices. / Takada, Shintaro; Kanba, Satoshi; Ogawa, Tetsuji et al.
2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA. 2007. p. 30-33 4393006 (IEEE Workshop on Applications of Signal Processing to Audio and Acoustics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Takada, S, Kanba, S, Ogawa, T, Akagiri, K & Kobayashi, T 2007, Sound source separation using null-beamforming and spectral subtraction for mobile devices. in 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA., 4393006, IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 30-33, 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA, New Paltz, NY, United States, 07/10/21. https://doi.org/10.1109/ASPAA.2007.4393006

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AB - This paper presents a new type of speech segregation method for mobile devices in noisy sound situation, where two or more speakers are talking simultaneously. The proposed method consists of multiple null-beamformers, their minimum power channel selection and spectral subtraction. The proposed method is performed with space-saving and coplanar microphone arrangements and low-cost calculations, which are the very important requirements for the mobile application. Effectiveness of the proposed method is clarified in the segregation and the recognition experiments of two simultaneous continuous speeches: the method improved the PESQ-based MOS value by about one point and reduced 70% of word recognition errors compared with non-processing.

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Sound source separation using null-beamforming and spectral subtraction for mobile devices

Abstract

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