Huaiping Ming — accepted AI-conference papers

2020

Improving Prosody with Linguistic and Bert Derived Features in Multi-Speaker Based Mandarin Chinese Neural TTS

Yujia Xiao, Lei He, Huaiping Ming, Frank K. Soong

ICASSP 2020accepted

Recent advances of neural TTS have made "human parity" synthesized speech possible when a large amount of studio-quality training data from a voice talent is available. However, with only limited, casual recordings from an ordinary speaker, human-like TTS is still a big challenge, in addition to oth…

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2016

Exemplar-based sparse representation of timbre and prosody for voice conversion

Huaiping Ming, Dong-Yan Huang, Lei Xie, Shaofei Zhang, Minghui Dong, Haizhou Li

ICASSP 2016accepted

Voice conversion (VC) aims to make one speaker (source) to sound like spoken by another speaker (target) without changing the language content. Most of the state-of-the-art voice conversion systems focus only on timbre conversion. However, the speaker identity is characterized by the source-related…

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