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C. Chien

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.AS4
same name
  • C. Chien — 27 papers, h 20
  • C. Chien — 14 papers, h 65
  • C. Chien — 5 papers, h 4
  • C. Chien — 2 papers, h 8
  • C. Chien — 2 papers, h 4
  • C. Chien — 2 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202022
collaborators

4 papers

eess.AS2022

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,…

eess.AS2021

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…

eess.AS2021

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…

eess.AS2020

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…

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