Deep autoregressive models with F0 discretization, post-processing, and self-attention prenet outperform RNNs in objective and subjective metrics for singing voice synthesis on a Chinese corpus.
Attention is all you need,
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Transformer and Memory Fusion Network attention mechanisms generalize to multimodal time-series emotion recognition on emotional autobiographical narratives, achieving performance comparable to human raters in some cases.
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Singing Voice Synthesis Using Deep Autoregressive Neural Networks for Acoustic Modeling
Deep autoregressive models with F0 discretization, post-processing, and self-attention prenet outperform RNNs in objective and subjective metrics for singing voice synthesis on a Chinese corpus.
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Attending to Emotional Narratives
Transformer and Memory Fusion Network attention mechanisms generalize to multimodal time-series emotion recognition on emotional autobiographical narratives, achieving performance comparable to human raters in some cases.