Papers by Jurgen Walle

1 papers
Enhancing Polyglot Voices by Leveraging Cross-Lingual Fine-Tuning in Any-to-One Voice Conversion (2024.findings-emnlp)

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Challenge: Recent advances in speech synthesis have improved the quality of polyglot voices.
Approach: They propose a cross-lingual any-to-one voice conversion system that preserves the source accent without multilingual data from the target speaker.
Outcome: The proposed system preserves source accent without multilingual data from target speaker and reduces training data requirements.

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