7 citations · 15 across the 6 of their papers we have counts for
6 papers
Beyond Shared Vocabulary: Increasing Representational Word Similarities across Languages for Multilingual Machine Translation
Di Wu, Christof Monz
Using a vocabulary that is shared across languages is common practice in Multilingual Neural Machine Translation (MNMT). In addition to its simple design, shared tokens play an imp…
Improving Neural Machine Translation by Bidirectional Training
Liang Ding, Di Wu, Dacheng Tao
We present a simple and effective pretraining strategy -- bidirectional training (BiT) for neural machine translation. Specifically, we bidirectionally update the model parameters…
The USYD-JD Speech Translation System for IWSLT 2021
Liang Ding, Di Wu, Dacheng Tao
This paper describes the University of Sydney& JD's joint submission of the IWSLT 2021 low resource speech translation task. We participated in the Swahili-English direction and go…
Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding
Di Wu, Yiren Chen, Liang Ding +1
Spoken language understanding (SLU) system usually consists of various pipeline components, where each component heavily relies on the results of its upstream ones. For example, In…
Context-Aware Cross-Attention for Non-Autoregressive Translation
Liang Ding, Longyue Wang, Di Wu +2
Non-autoregressive translation (NAT) significantly accelerates the inference process by predicting the entire target sequence. However, due to the lack of target dependency modelli…
SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling
Di Wu, Liang Ding, Fan Lu +1
Slot filling and intent detection are two main tasks in spoken language understanding (SLU) system. In this paper, we propose a novel non-autoregressive model named SlotRefine for…