no code implementations • 20 May 2022 • Wenxuan Wang, Wenxiang Jiao, Shuo Wang, Zhaopeng Tu, Michael R. Lyu
Zero-shot translation is a promising direction for building a comprehensive multilingual neural machine translation (MNMT) system.
no code implementations • ACL 2022 • Wenxuan Wang, Wenxiang Jiao, Yongchang Hao, Xing Wang, Shuming Shi, Zhaopeng Tu, Michael Lyu
In this paper, we present a substantial step in better understanding the SOTA sequence-to-sequence (Seq2Seq) pretraining for neural machine translation~(NMT).
1 code implementation • ACL 2021 • Wenxiang Jiao, Xing Wang, Zhaopeng Tu, Shuming Shi, Michael R. Lyu, Irwin King
In this work, we propose to improve the sampling procedure by selecting the most informative monolingual sentences to complement the parallel data.
1 code implementation • NAACL 2021 • Yongchang Hao, Shilin He, Wenxiang Jiao, Zhaopeng Tu, Michael Lyu, Xing Wang
In addition, experimental results demonstrate that our Multi-Task NAT is complementary to knowledge distillation, the standard knowledge transfer method for NAT.
1 code implementation • EMNLP 2020 • Wenxiang Jiao, Xing Wang, Shilin He, Irwin King, Michael R. Lyu, Zhaopeng Tu
First, we train an identification model on the original training data, and use it to distinguish inactive examples and active examples by their sentence-level output probabilities.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Wenxiang Jiao, Michael R. Lyu, Irwin King
Emotion Recognition in Conversations (ERC) aims to predict the emotional state of speakers in conversations, which is essentially a text classification task.
1 code implementation • 20 Nov 2019 • Wenxiang Jiao, Michael R. Lyu, Irwin King
We propose an Attention Gated Hierarchical Memory Network (AGHMN) to address the problems of prior work: (1) Commonly used convolutional neural networks (CNNs) for utterance feature extraction are less compatible in the memory modules; (2) Unidirectional gated recurrent units (GRUs) only allow each historical utterance to have context before it, preventing information propagation in the opposite direction; (3) The Soft Attention for summarizing loses the positional and ordering information of memories, regardless of how the memory bank is built.
Ranked #24 on
Emotion Recognition in Conversation
on IEMOCAP
no code implementations • 21 Oct 2019 • Wenxiang Jiao, Irwin King, Michael R. Lyu
Word2Vec is the most popular model for word representation and has been widely investigated in literature.
1 code implementation • 20 Oct 2019 • Wenxiang Jiao, Michael R. Lyu, Irwin King
Witnessing the success of transfer learning in natural language process (NLP), we propose to pre-train a context-dependent encoder (CoDE) for ULER by learning from unlabeled conversation data.
1 code implementation • NAACL 2019 • Wenxiang Jiao, Haiqin Yang, Irwin King, Michael R. Lyu
In this paper, we address three challenges in utterance-level emotion recognition in dialogue systems: (1) the same word can deliver different emotions in different contexts; (2) some emotions are rarely seen in general dialogues; (3) long-range contextual information is hard to be effectively captured.