A Novel Method to Correct Steering Vectors in MVDR Beamformer for Noise Robust ASR

Suliang Bu, Yunxin Zhao, Mei-Yuh Hwang


Accurate steering vectors (SV) are key to many beamformers. However, reliable SV is not easy to obtain. In this work, we investigate a novel method to identify and correct phase errors in SV for MVDR beamforming. Our idea stems from the linear relationship in the phase of a microphone component in narrowband SVs across frequency, as modeled by acoustic transfer function. We utilize this property and feedforward neural nets to make phase prediction for the microphone components in SVs, and use the predicted phase selectively for phase error correction and MVDR beamforming. Our method is robust to large fluctuations in phase spectrum wrapped within [-π, π]. We have evaluated our approach on CHiME-3 and obtained improved performances on both word error rate and short-time objective intelligibility in low reverberant acoustic environments.


 DOI: 10.21437/Interspeech.2019-2944

Cite as: Bu, S., Zhao, Y., Hwang, M. (2019) A Novel Method to Correct Steering Vectors in MVDR Beamformer for Noise Robust ASR. Proc. Interspeech 2019, 4280-4284, DOI: 10.21437/Interspeech.2019-2944.


@inproceedings{Bu2019,
  author={Suliang Bu and Yunxin Zhao and Mei-Yuh Hwang},
  title={{A Novel Method to Correct Steering Vectors in MVDR Beamformer for Noise Robust ASR}},
  year=2019,
  booktitle={Proc. Interspeech 2019},
  pages={4280--4284},
  doi={10.21437/Interspeech.2019-2944},
  url={http://dx.doi.org/10.21437/Interspeech.2019-2944}
}