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Beamformer performance with acoustic vector sensors in air
Michael E Lockwood1, Douglas L Jones
1Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 North Mathews Avenue, Urbana, Illinois 61801, USA. melockwo@uiuc.edu
The Journal of the Acoustical Society of America
|February 4, 2006
Summary
This study demonstrates that a compact acoustic vector sensor (AVS) using a four-microphone array significantly improves signal-to-noise ratio (SNR) for speech source separation in noisy environments.
Area of Science:
- Acoustics
- Signal Processing
- Microphone Array Technology
Background:
- Acoustic vector sensors (AVSs) are used underwater for particle velocity sensing.
- AVSs offer potential for noise reduction in air with small apertures and fewer channels.
Purpose of the Study:
- To evaluate the signal extraction performance of adaptive beamforming algorithms using a compact AVS in air.
- To compare the performance of different beamforming techniques for speech source separation.
Main Methods:
- Constructed a four-microphone array approximating a small AVS (1 cm3) with gradient and omnidirectional microphones.
- Processed test signals with two to five speech sources using nonadaptive and adaptive beamforming algorithms.
- Quantified performance by calculating the output signal-to-noise ratio (SNR).
Main Results:
- Frequency-domain minimum-variance (FMV) beamformers achieved 11-14 dB SNR improvement with a three-microphone array.
- Generalized sidelobe canceller (GSC) yielded 5.5-8.5 dB SNR improvement.
- The compact AVS outperformed a traditional two-microphone omnidirectional array.
Conclusions:
- Compact AVSs with adaptive beamforming show significant potential for enhanced speech intelligibility in noisy air environments.
- The evaluated beamforming algorithms demonstrate effective noise reduction and source separation capabilities.
- This technology offers advantages over conventional microphone arrays for acoustic sensing applications.