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Improving End-To-End Speech Synthesis With Local Recurrent Neural Network Enhanced Transformer
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Improving End-To-End Speech Synthesis With Local Recurrent Neural Network Enhanced Transformer
Although Transformer based neural end-to-end TTS model has demonstrated extreme effectiveness in capturing long-term dependencies and achieved state-of-the-art performance, it still suffers from two problems. 1) limited ability to model sequential and loc
Although Transformer based neural end-to-end TTS model has demonstrated extreme effectiveness in capturing long-term dependencies and achieved state-of-the-art performance, it still suffers from two problems. 1) limited ability to model sequential and loc
