40 citations · 188 across the 22 of their papers we have counts for
7 papers · 1 filter
Empowering Diffusion Models on the Embedding Space for Text Generation
Zhujin Gao, Junliang Guo, Xu Tan +4
Diffusion models have achieved state-of-the-art synthesis quality on both visual and audio tasks, and recent works further adapt them to textual data by diffusing on the embedding…
VideoDubber: Machine Translation with Speech-Aware Length Control for Video Dubbing
Yihan Wu, Junliang Guo, Xu Tan +7
Video dubbing aims to translate the original speech in a film or television program into the speech in a target language, which can be achieved with a cascaded system consisting of…
Bridging Music and Text with Crowdsourced Music Comments: A Sequence-to-Sequence Framework for Thematic Music Comments Generation
Peining Zhang, Junliang Guo, Linli Xu +2
We consider a novel task of automatically generating text descriptions of music. Compared with other well-established text generation tasks such as image caption, the scarcity of w…
A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation
Kexun Zhang, Rui Wang, Xu Tan +4
It is difficult for non-autoregressive translation (NAT) models to capture the multi-modal distribution of target translations due to their conditional independence assumption, whi…
Sequence-to-Action: Grammatical Error Correction with Action Guided Sequence Generation
Jiquan Li, Junliang Guo, Yongxin Zhu +4
The task of Grammatical Error Correction (GEC) has received remarkable attention with wide applications in Natural Language Processing (NLP) in recent years. While one of the key p…
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis
Yichong Leng, Zehua Chen, Junliang Guo +9
Binaural audio plays a significant role in constructing immersive augmented and virtual realities. As it is expensive to record binaural audio from the real world, synthesizing the…
A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond
Yisheng Xiao, Lijun Wu, Junliang Guo +4
Non-autoregressive (NAR) generation, which is first proposed in neural machine translation (NMT) to speed up inference, has attracted much attention in both machine learning and na…