Papers by Giuseppe Ruggiero
Eta-WavLM: Efficient Speaker Identity Removal in Self-Supervised Speech Representations Using a Simple Linear Equation (2025.findings-acl)
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| Challenge: | Existing methods for learning meaningful representations from unannotated data are resource-intensive and degrade other speech components. |
| Approach: | They propose a method that decomposes SSL representations into speaker-specific components and generates speaker disentangled representations. |
| Outcome: | The proposed method achieves speaker independence and improves on state-of-the-art methods. |
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. |