1.5k citations · 1.5k across the 14 of their papers we have counts for
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Controllable Emotion Transfer For End-to-End Speech Synthesis
Tao Li, Shan Yang, Liumeng Xue +1
Emotion embedding space learned from references is a straightforward approach for emotion transfer in encoder-decoder structured emotional text to speech (TTS) systems. However, th…
Accent and Speaker Disentanglement in Many-to-many Voice Conversion
Zhichao Wang, Wenshuo Ge, Xiong Wang +6
This paper proposes an interesting voice and accent joint conversion approach, which can convert an arbitrary source speaker's voice to a target speaker with non-native accent. Thi…
Fine-grained Emotion Strength Transfer, Control and Prediction for Emotional Speech Synthesis
Yi Lei, Shan Yang, Lei Xie
This paper proposes a unified model to conduct emotion transfer, control and prediction for sequence-to-sequence based fine-grained emotional speech synthesis. Conventional emotion…
Learn2Sing: Target Speaker Singing Voice Synthesis by learning from a Singing Teacher
Heyang Xue, Shan Yang, Yi Lei +2
Singing voice synthesis has been paid rising attention with the rapid development of speech synthesis area. In general, a studio-level singing corpus is usually necessary to produc…
Exploiting Deep Sentential Context for Expressive End-to-End Speech Synthesis
Fengyu Yang, Shan Yang, Qinghua Wu +2
Attention-based seq2seq text-to-speech systems, especially those use self-attention networks (SAN), have achieved state-of-art performance. But an expressive corpus with rich proso…
Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speech
Geng Yang, Shan Yang, Kai Liu +3
In this paper, we propose multi-band MelGAN, a much faster waveform generation model targeting to high-quality text-to-speech. Specifically, we improve the original MelGAN by the f…
Adversarial Feature Learning and Unsupervised Clustering based Speech Synthesis for Found Data with Acoustic and Textual Noise
Shan Yang, Yuxuan Wang, Lei Xie
Attention-based sequence-to-sequence (seq2seq) speech synthesis has achieved extraordinary performance. But a studio-quality corpus with manual transcription is necessary to train…