Multi-Microphone Adaptive Noise Cancellation for Robust Hotword Detection

Yiteng Huang, Turaj Z. Shabestary, Alexander Gruenstein, Li Wan


Recently we proposed a dual-microphone adaptive noise cancellation (ANC) algorithm with deferred filter coefficients for robust hotword detection in [1]. It exploits two unique hotword-related features: hotwords are the leading phrase of valid voice queries and they are short. These features allow us not to compute a speech-noise mask that is a common prerequisite for many multichannel speech enhancement approaches. This novel idea was found effective against strong and ambiguous speech-like TV noise. In this paper, we show that it can be generalized to support more than two microphones. The development is validated using re-recorded data with background TV noise from a 3-mic array. By adding one more microphone, the false reject (FR) rate can be further reduced relatively by 33.5%.


 DOI: 10.21437/Interspeech.2019-3006

Cite as: Huang, Y., Shabestary, T.Z., Gruenstein, A., Wan, L. (2019) Multi-Microphone Adaptive Noise Cancellation for Robust Hotword Detection. Proc. Interspeech 2019, 1233-1237, DOI: 10.21437/Interspeech.2019-3006.


@inproceedings{Huang2019,
  author={Yiteng Huang and Turaj Z. Shabestary and Alexander Gruenstein and Li Wan},
  title={{Multi-Microphone Adaptive Noise Cancellation for Robust Hotword Detection}},
  year=2019,
  booktitle={Proc. Interspeech 2019},
  pages={1233--1237},
  doi={10.21437/Interspeech.2019-3006},
  url={http://dx.doi.org/10.21437/Interspeech.2019-3006}
}