58 citations · 76 across the 14 of their papers we have counts for
14 papers
Joint Training And Decoding for Multilingual End-to-End Simultaneous Speech Translation
Wuwei Huang, Renren Jin, Wen Zhang +3
Recent studies on end-to-end speech translation(ST) have facilitated the exploration of multilingual end-to-end ST and end-to-end simultaneous ST. In this paper, we investigate end…
Exploring Better Text Image Translation with Multimodal Codebook
Zhibin Lan, Jiawei Yu, Xiang Li +5
Text image translation (TIT) aims to translate the source texts embedded in the image to target translations, which has a wide range of applications and thus has important research…
Rethinking the Reasonability of the Test Set for Simultaneous Machine Translation
Mengge Liu, Wen Zhang, Xiang Li +4
Simultaneous machine translation (SimulMT) models start translation before the end of the source sentence, making the translation monotonically aligned with the source sentence. Ho…
BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation
Xiangyu Qin, Zhiyu Wu, Jinshi Cui +5
Previous works on emotion recognition in conversation (ERC) follow a two-step paradigm, which can be summarized as first producing context-independent features via fine-tuning pret…
MoralDial: A Framework to Train and Evaluate Moral Dialogue Systems via Moral Discussions
Hao Sun, Zhexin Zhang, Fei Mi +6
Morality in dialogue systems has raised great attention in research recently. A moral dialogue system aligned with users' values could enhance conversation engagement and user conn…
C3KG: A Chinese Commonsense Conversation Knowledge Graph
Dawei Li, Yanran Li, Jiayi Zhang +4
Existing commonsense knowledge bases often organize tuples in an isolated manner, which is deficient for commonsense conversational models to plan the next steps. To fill the gap,…
MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation
Quan Tu, Yanran Li, Jianwei Cui +3
Applying existing methods to emotional support conversation -- which provides valuable assistance to people who are in need -- has two major limitations: (a) they generally employ…
Multi-Scale Local-Temporal Similarity Fusion for Continuous Sign Language Recognition
Pan Xie, Zhi Cui, Yao Du +4
Continuous sign language recognition (cSLR) is a public significant task that transcribes a sign language video into an ordered gloss sequence. It is important to capture the fine-…
Improving Tree-Structured Decoder Training for Code Generation via Mutual Learning
Binbin Xie, Jinsong Su, Yubin Ge +4
Code generation aims to automatically generate a piece of code given an input natural language utterance. Currently, among dominant models, it is treated as a sequence-to-tree task…
Towards an Online Empathetic Chatbot with Emotion Causes
Yanran Li, Ke Li, Hongke Ning +5
Existing emotion-aware conversational models usually focus on controlling the response contents to align with a specific emotion class, whereas empathy is the ability to understand…
Modeling Homophone Noise for Robust Neural Machine Translation
Wenjie Qin, Xiang Li, Yuhui Sun +3
In this paper, we propose a robust neural machine translation (NMT) framework. The framework consists of a homophone noise detector and a syllable-aware NMT model to homophone erro…
Reasoning in Dialog: Improving Response Generation by Context Reading Comprehension
Xiuying Chen, Zhi Cui, Jiayi Zhang +5
In multi-turn dialog, utterances do not always take the full form of sentences \cite{Carbonell1983DiscoursePA}, which naturally makes understanding the dialog context more difficul…
Infusing Sequential Information into Conditional Masked Translation Model with Self-Review Mechanism
Pan Xie, Zhi Cui, Xiuyin Chen +3
Non-autoregressive models generate target words in a parallel way, which achieve a faster decoding speed but at the sacrifice of translation accuracy. To remedy a flawed translatio…
Modeling Discourse Structure for Document-level Neural Machine Translation
Junxuan Chen, Xiang Li, Jiarui Zhang +4
Recently, document-level neural machine translation (NMT) has become a hot topic in the community of machine translation. Despite its success, most of existing studies ignored the…