SegINR: Segment-wise Implicit Neural Representation for Sequence Alignment in Neural Text-to-Speech

We present SegINR, a novel approach to neural Text-to-Speech (TTS) that addresses sequence alignment without relying on an auxiliary duration predictor and complex autoregressive (AR) or non-autoregressive (NAR) frame-level sequence modeling. SegINR simplifies the process by converting text sequence...

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Hauptverfasser:	Kim, Minchan, Jeong, Myeonghun, Lee, Joun Yeop, Kim, Nam Soo
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning
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