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Voice Conversion Challenge 2020 –- Intra-lingual semi-parallel and cross-lingual voice conversion –-
Open accessAbstract
The voice conversion challenge is a bi-annual scientific event held to compare and understand different voice conversion (VC) systems built on a common dataset.In 2020, we organized the third edition of the challenge and constructed and distributed a new database for two tasks, intra-lingual semiparallel and cross-lingual VC.After a two-month challenge period, we received 33 submissions, including 3 baselines built on the database.From the results of crowd-sourced listening tests, we observed that VC methods have progressed rapidly thanks to advanced deep learning methods.In particular, speaker similarity scores of several systems turned out to be as high as target speakers in the intra-lingual semi-parallel VC task.However, we confirmed that none of them have achieved human-level naturalness yet for the same task.The cross-lingual conversion task is, as expected, a more difficult task, and the overall naturalness and similarity scores were lower than those for the intra-lingual conversion task.However, we observed encouraging results, and the MOS scores of the best systems were higher than 4.0.We also show a few additional analysis results to aid in understanding cross-lingual VC better.
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Metadata
- Authors
- Yi, Z., Huang, W.-C., Tian, X., Yamagishi, J., Das, R. K., Kinnunen, T., Ling, Z.-H., & Toda, T.
- Affiliations
- National Institute of Informatics (JP)
- Nagoya University (JP)
- National University of Singapore (SG)
- University of Eastern Finland (FI)
- University of Science and Technology of China (CN)
- ORCID
- Venue
- Joint Workshop for the Blizzard Challenge and Voice Conversion Challenge 2020
- Publisher
- ISCA
- Published
- 2020-10-30
- Pages
- 80-98
- OpenAlex
- W3082130377
- Cited by
- 126
- References
- 54
- Citations by year
- 2026: 6 · 2025: 17 · 2024: 9 · 2023: 27 · 2022: 26 · 2021: 33 · 2020: 8
- FWCI
- 8.85
- Type
- conference paper
- Language
- en
- Open access
- gold
- doi.org
- Funders
- National Research Foundation
- Ministry of Education, Culture, Sports, Science and Technology (18H04112, 17H04687, 16H06302, 18H04120, 18KT0051, CREST)
- National Natural Science Foundation of China (JPMJCR19A3, 61871358)
- Japan Society for the Promotion of Science (17H06101, 19K24373, JPMJCR18A6, 18H04120, 18H04112, CREST, 16H06302, 17H04687, 18KT0051)
- Core Research for Evolutional Science and Technology (JP-MJCR19A3, JPMJCR18A6)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Health Sciences › Health Professions › Speech and Hearing › Voice and Speech Disorders
- Keywords
- voice conversion, cross-lingual voice conversion, listening tests, speaker similarity, naturalness, deep learning
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