Corpus ID: 209531933

Temporal-Spatial Neural Filter: Direction Informed End-to-End Multi-channel Target Speech Separation

  title={Temporal-Spatial Neural Filter: Direction Informed End-to-End Multi-channel Target Speech Separation},
  author={R. Gu and Yuexian Zou},
  • R. Gu, Yuexian Zou
  • Published 2020
  • Computer Science, Engineering
  • ArXiv
  • Target speech separation refers to extracting the target speaker's speech from mixed signals. Despite the recent advances in deep learning based close-talk speech separation, the applications to real-world are still an open issue. Two main challenges are the complex acoustic environment and the real-time processing requirement. To address these challenges, we propose a temporal-spatial neural filter, which directly estimates the target speech waveform from multi-speaker mixture in reverberant… CONTINUE READING


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