Search Results for author: Dongyang Dai

Found 5 papers, 1 papers with code

RFWave: Multi-band Rectified Flow for Audio Waveform Reconstruction

1 code implementation8 Mar 2024 Peng Liu, Dongyang Dai

Recent advancements in generative modeling have led to significant progress in audio waveform reconstruction from diverse representations.

Computational Efficiency

Unsupervised Cross-Lingual Speech Emotion Recognition Using DomainAdversarial Neural Network

no code implementations21 Dec 2020 Xiong Cai, Zhiyong Wu, Kuo Zhong, Bin Su, Dongyang Dai, Helen Meng

By using deep learning approaches, Speech Emotion Recog-nition (SER) on a single domain has achieved many excellentresults.

Speech Emotion Recognition

Speaker Independent and Multilingual/Mixlingual Speech-Driven Talking Head Generation Using Phonetic Posteriorgrams

no code implementations20 Jun 2020 Huirong Huang, Zhiyong Wu, Shiyin Kang, Dongyang Dai, Jia Jia, Tianxiao Fu, Deyi Tuo, Guangzhi Lei, Peng Liu, Dan Su, Dong Yu, Helen Meng

Recent approaches mainly have following limitations: 1) most speaker-independent methods need handcrafted features that are time-consuming to design or unreliable; 2) there is no convincing method to support multilingual or mixlingual speech as input.

Talking Head Generation

Noise Robust TTS for Low Resource Speakers using Pre-trained Model and Speech Enhancement

no code implementations26 May 2020 Dongyang Dai, Li Chen, Yu-Ping Wang, Mu Wang, Rui Xia, Xuchen Song, Zhiyong Wu, Yuxuan Wang

Firstly, the speech synthesis model is pre-trained with both multi-speaker clean data and noisy augmented data; then the pre-trained model is adapted on noisy low-resource new speaker data; finally, by setting the clean speech condition, the model can synthesize the new speaker's clean voice.

Speech Enhancement Speech Synthesis

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