2019
Enhancing Hybrid Self-attention Structure with Relative-position-aware Bias for Speech Synthesis
ICASSP 2019accepted
Compared with the conventional "front-end"-"back-end"- "vocoder" structure, based on the attention mechanism, end-to-end speech synthesis systems directly train and synthesize from text sequence to the acoustic feature sequence as a whole. Recently, a more calculation efficient end-to-end architectu…