进化计算的IEEE期刊TEC(IEEE Transactions on Evolutionary Computation)出版高质量的进化计算和相关领域的原始文献,包括自然启发算法、基于种群的方法、选择和变异不可分割的优化以及混合系统。纯理论论文被认为是提供这些计算领域一般见解的应用论文。本杂志的文章按照IEEE PSPB操作手册(章节8.2.1.C和8.2.2.A)的要求进行同行评审。每一篇发表的文章都由至少两名独立的审稿人通过单盲的同行评审过程进行评审。 官网地址:http://dblp.uni-trier.de/db/journals/tec/

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In this paper, we propose Textual Echo Cancellation (TEC) - a framework for cancelling the text-to-speech (TTS) playback echo from overlapping 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 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 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 or 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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