A Microphone Array Beamformer for the Performance Enhancement of Speech Recognizer in Car

In this paper, a microphone array beamforming algorithm that reduces the signal distortion caused by reverberation and near-field effect in car environment is proposed. When reverberation or near-field effect is present, an optimum beamformer should be constructed with a steering vector consisting of transfer functions between source and microphones, but it is generally difficult to estimate transfer functions on-line without knowledge of the source signal. Instead, a sub-optimal beamforming algorithm that reduces signal distortion is proposed. It is constructed with steering vectors consisting of relative transfer functions between reference sensor and other sensors. In order to evaluate the performance of the proposed algorithm, we had recorded noisy speech database in a car, and performed speech recognition experiments with HIVIM Toolkit (HTK) released by Cambridge University. The recognition rate of the proposed algorithm was 15 percents higher than that of the conventional far-field beamformers in best case.