6 citations · 18 across the 7 of their papers we have counts for
7 papers
Improving End-to-end Speech Translation by Leveraging Auxiliary Speech and Text Data
Yuhao Zhang, Chen Xu, Bojie Hu +3
We present a method for introducing a text encoder into pre-trained end-to-end speech translation systems. It enhances the ability of adapting one modality (i.e., source-language s…
Continual Learning of Neural Machine Translation within Low Forgetting Risk Regions
Shuhao Gu, Bojie Hu, Yang Feng
This paper considers continual learning of large-scale pretrained neural machine translation model without accessing the previous training data or introducing model separation. We…
Increasing Visual Awareness in Multimodal Neural Machine Translation from an Information Theoretic Perspective
Baijun Ji, Tong Zhang, Yicheng Zou +2
Multimodal machine translation (MMT) aims to improve translation quality by equipping the source sentence with its corresponding image. Despite the promising performance, MMT model…
Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders
Chen Xu, Bojie Hu, Yanyang Li +5
Encoder pre-training is promising in end-to-end Speech Translation (ST), given the fact that speech-to-translation data is scarce. But ST encoders are not simple instances of Autom…
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation
Chen Xu, Bojie Hu, Yufan Jiang +6
Large amounts of data has made neural machine translation (NMT) a big success in recent years. But it is still a challenge if we train these models on small-scale corpora. In this…
Code-switching pre-training for neural machine translation
Zhen Yang, Bojie Hu, Ambyera Han +2
This paper proposes a new pre-training method, called Code-Switching Pre-training (CSP for short) for Neural Machine Translation (NMT). Unlike traditional pre-training method which…
Learn to Segment Retinal Lesions and Beyond
Qijie Wei, Xirong Li, Weihong Yu +8
Towards automated retinal screening, this paper makes an endeavor to simultaneously achieve pixel-level retinal lesion segmentation and image-level disease classification. Such a m…