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eess.AS2024
MakeSinger: A Semi-Supervised Training Method for Data-Efficient Singing Voice Synthesis via Classifier-free Diffusion Guidance
Semin Kim, Myeonghun Jeong, Hyeonseung Lee +3
In this paper, we propose MakeSinger, a semi-supervised training method for singing voice synthesis (SVS) via classifier-free diffusion guidance. The challenge in SVS lies in the c…
eess.AS2024
Utilizing Neural Transducers for Two-Stage Text-to-Speech via Semantic Token Prediction
Minchan Kim, Myeonghun Jeong, Byoung Jin Choi +3
We propose a novel text-to-speech (TTS) framework centered around a neural transducer. Our approach divides the whole TTS pipeline into semantic-level sequence-to-sequence (seq2seq…