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    <h1>Textual Echo Cancellation</h1>
    <p><b>Paper:</b> <a href="https://arxiv.org/abs/2008.06006">arXiv</a></p>
    <p><b>Authors:</b> Shaojin Ding, Ye Jia, Ke Hu, Quan Wang</p>

    <p><b>Abstract:</b>
      In this paper, we propose Textual Echo Cancellation (TEC) - a framework for cancelling the text-to-speech (TTS)
      playback echo from overlapped speech recordings. Such a system can largely improve speech recognition performance
      and user experience for intelligent devices such as smart speakers, as the user can talk to the device while the
      device is still playing the TTS signal responding to the previous query. We implement this system by using a novel
      sequence-to-sequence model with multi-source attention that takes both the microphone mixture signal and the
      source text of the TTS playback as inputs, and predicts the enhanced audio. Experiments show that the textual
      information of the TTS playback is critical to the enhancement performance. Besides, the text sequence is much
      smaller in size compared with the raw acoustic signal of the TTS playback, and can be immediately transmitted to
      the device and the ASR server even before the playback is synthesized. Therefore, our proposed approach
      effectively reduces Internet communication and latency compared with alternative approaches such as acoustic echo
      cancellation (AEC).
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