121 citations · 179 across the 17 of their papers we have counts for
17 papers
Multi-modal Domain Adaptation for REG via Relation Transfer
Yifan Ding, Liqiang Wang, Boqing Gong
Domain adaptation, which aims to transfer knowledge between domains, has been well studied in many areas such as image classification and object detection. However, for multi-modal…
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…
Miipher: A Robust Speech Restoration Model Integrating Self-Supervised Speech and Text Representations
Yuma Koizumi, Heiga Zen, Shigeki Karita +7
Speech restoration (SR) is a task of converting degraded speech signals into high-quality ones. In this study, we propose a robust SR model called Miipher, and apply Miipher to a n…
Residual Adapters for Few-Shot Text-to-Speech Speaker Adaptation
Nobuyuki Morioka, Heiga Zen, Nanxin Chen +2
Adapting a neural text-to-speech (TTS) model to a target speaker typically involves fine-tuning most if not all of the parameters of a pretrained multi-speaker backbone model. Howe…
H-EMD: A Hierarchical Earth Mover's Distance Method for Instance Segmentation
Peixian Liang, Yizhe Zhang, Yifan Ding +5
Deep learning (DL) based semantic segmentation methods have achieved excellent performance in biomedical image segmentation, producing high quality probability maps to allow extrac…
Leveraging unsupervised and weakly-supervised data to improve direct speech-to-speech translation
Ye Jia, Yifan Ding, Ankur Bapna +4
End-to-end speech-to-speech translation (S2ST) without relying on intermediate text representations is a rapidly emerging frontier of research. Recent works have demonstrated that…