3 papers
cs.CL2024
Adaptive Dropout for Pruning Conformers
Yotaro Kubo, Xingyu Cai, Michiel Bacchiani
This paper proposes a method to effectively perform joint training-and-pruning based on adaptive dropout layers with unit-wise retention probabilities. The proposed method is based…
cs.CL2024
FLEURS-R: A Restored Multilingual Speech Corpus for Generation Tasks
Min Ma, Yuma Koizumi, Shigeki Karita +4
This paper introduces FLEURS-R, a speech restoration applied version of the Few-shot Learning Evaluation of Universal Representations of Speech (FLEURS) corpus. FLEURS-R maintains…
eess.AS2023
LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus
Yuma Koizumi, Heiga Zen, Shigeki Karita +7
This paper introduces a new speech dataset called ``LibriTTS-R'' designed for text-to-speech (TTS) use. It is derived by applying speech restoration to the LibriTTS corpus, which c…