Beamforming and maximum likelihood estimation for speech enhancement using dual closely-spaced microphones

doi:10.16511/j.cnki.qhdxxb.2018.26.027

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Abstract Traditional beamforming systems using dual closely-spaced microphones have various problems such as low-frequency-roll-off and limitations in suppressing competitive speech noises from multiple directions. This paper presents a two-step beamforming and maximum likelihood estimation algorithm. The algorithm first uses a WOLA filter for the time-frequency analysis for the speech mixture and then sets mask values to suppress background noise without low-frequency-roll-off based on the ratio of the two beamforming patterns, which have zeros at 0ånd 180°. A statistical model and the maximum likelihood estimation are then used to further enhance the speech. Tests indicate that the algorithm effectively recovers the energy distribution of the target signal and improves the signal-to-noise ratio without a low-pass filter or broadband compensation when the signal-to-ratio is low or multiple kinds of noises exist.

Keywords closely-spaced dual microphones beamforming maximum likelihood estimation low-frequency roll-off competitive speech noises from multiple directions

Issue Date: 15 June 2018

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	GONG Qin
	ZHENG Shuo

Cite this article:

GONG Qin,ZHENG Shuo. Beamforming and maximum likelihood estimation for speech enhancement using dual closely-spaced microphones[J]. Journal of Tsinghua University(Science and Technology), 2018, 58(6): 603-608.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2018.26.027 OR http://jst.tsinghuajournals.com/EN/Y2018/V58/I6/603

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