StarGAN-VC： non-parallel many-to-many voice conversion with StaGAN
会议：2018 IEEE Spoken Language Technology Workshop (SLT) 单位：NTT 作者：Hirokazu Kameoka, Takuhiro Kaneko abstract 本文提出StarGAN，优点：（1）no need of parallel data, transcription, time-alignment；（2）一个生成器学习many-t
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相关文章
- 1. SINGING VOICE CONVERSION WITH NON-PARALLEL DATA
- 2. ONE-SHOT VOICE CONVERSION USING STAR-GAN
- 3. Voice Conversion by Cascading Automatic Speech Recognition and Text-to-Speech Synthesis with Prosody
- 4. Odessey2018:Average Modeling Approach to Voice Conversion with Non-Parallel Data
- 5. Many-to-many Cross-lingual Voice Conversion with a Jointly Trained Speaker Embedding Network
- 6. 2019icas--Cross-lingual Voice Conversion with Bilingual Phonetic PosteriorGram and Average Modeling
- 7. 2019trans--Sequence-to-Sequence Acoustic Modeling for Voice Conversion
- 8. StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion
- 9. Voice Conversion using Convolutional Neural Networks 翻译
- 10. Neural Voice Cloning with a Few Samples