• Corpus ID: 239049687

TPARN: Triple-path Attentive Recurrent Network for Time-domain Multichannel Speech Enhancement

@article{Pandey2021TPARNTA,
  title={TPARN: Triple-path Attentive Recurrent Network for Time-domain Multichannel Speech Enhancement},
  author={Ashutosh Pandey and Buye Xu and Anurag Kumar and Jacob Donley and Paul T. Calamia and Deliang Wang},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.10757}
}
In this work, we propose a new model called triple-path attentive recurrent network (TPARN) for multichannel speech enhancement in the time domain. TPARN extends a single-channel dual-path network to a multichannel network by adding a third path along the spatial dimension. First, TPARN processes speech signals from all channels independently using a dual-path attentive recurrent network (ARN), which is a recurrent neural network (RNN) augmented with self-attention. Next, an ARN is introduced… 

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References

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