3 citations · 7 across the 5 of their papers we have counts for
6 papers
What Do Self-Supervised Speech Models Know About Words?
Ankita Pasad, Chung-Ming Chien, Shane Settle +1
Many self-supervised speech models (S3Ms) have been introduced over the last few years, improving performance and data efficiency on various speech tasks. However, these empirical…
Voice Filter: Few-shot text-to-speech speaker adaptation using voice conversion as a post-processing module
Adam Gabryś, Goeric Huybrechts, Manuel Sam Ribeiro +6
State-of-the-art text-to-speech (TTS) systems require several hours of recorded speech data to generate high-quality synthetic speech. When using reduced amounts of training data,…
Investigating on Incorporating Pretrained and Learnable Speaker Representations for Multi-Speaker Multi-Style Text-to-Speech
Chung-Ming Chien, Jheng-Hao Lin, Chien-yu Huang +2
The few-shot multi-speaker multi-style voice cloning task is to synthesize utterances with voice and speaking style similar to a reference speaker given only a few reference sample…
S2VC: A Framework for Any-to-Any Voice Conversion with Self-Supervised Pretrained Representations
Jheng-hao Lin, Yist Y. Lin, Chung-Ming Chien +1
Any-to-any voice conversion (VC) aims to convert the timbre of utterances from and to any speakers seen or unseen during training. Various any-to-any VC approaches have been propos…
Hierarchical Prosody Modeling for Non-Autoregressive Speech Synthesis
Chung-Ming Chien, Hung-yi Lee
Prosody modeling is an essential component in modern text-to-speech (TTS) frameworks. By explicitly providing prosody features to the TTS model, the style of synthesized utterances…
FragmentVC: Any-to-Any Voice Conversion by End-to-End Extracting and Fusing Fine-Grained Voice Fragments With Attention
Yist Y. Lin, Chung-Ming Chien, Jheng-Hao Lin +2
Any-to-any voice conversion aims to convert the voice from and to any speakers even unseen during training, which is much more challenging compared to one-to-one or many-to-many ta…