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Investigating Self-supervised Pretraining Frameworks for Pathological Speech Recognition., , and . INTERSPEECH, page 41-45. ISCA, (2022)Electrolaryngeal Speech Intelligibility Enhancement through Robust Linguistic Encoders., , , , , and . ICASSP, page 10961-10965. IEEE, (2024)Improving Severity Preservation of Healthy-to-Pathological Voice Conversion With Global Style Tokens., , , , and . ASRU, page 1-7. IEEE, (2023)Towards Identity Preserving Normal to Dysarthric Voice Conversion., , , , and . ICASSP, page 6672-6676. IEEE, (2022)Two-Stage Training Method for Japanese Electrolaryngeal Speech Enhancement Based on Sequence-to-Sequence Voice Conversion., , , and . SLT, page 949-954. IEEE, (2022)A Comparative Study of Voice Conversion Models With Large-Scale Speech and Singing Data: The T13 Systems for the Singing Voice Conversion Challenge 2023., , , , and . ASRU, page 1-6. IEEE, (2023)Pretraining and Adaptation Techniques for Electrolaryngeal Speech Recognition., , , and . IEEE ACM Trans. Audio Speech Lang. Process., (2024)Intermediate Fine-Tuning Using Imperfect Synthetic Speech for Improving Electrolaryngeal Speech Recognition., , , and . ICASSP, page 1-5. IEEE, (2023)A Preliminary Investigation on Flexible Singing Voice Synthesis Through Decomposed Framework with Inferrable Features., and . CoRR, (2024)The Singing Voice Conversion Challenge 2023., , , , and . ASRU, page 1-8. IEEE, (2023)