138 citations · 480 across the 46 of their papers we have counts for
8 papers · 2 filters
Adversarial Advantage Actor-Critic Model for Task-Completion Dialogue Policy Learning
Baolin Peng, Xiujun Li, Jianfeng Gao +3
This paper presents a new method --- adversarial advantage actor-critic (Adversarial A2C), which significantly improves the efficiency of dialogue policy learning in task-completio…
Dynamic Time-Aware Attention to Speaker Roles and Contexts for Spoken Language Understanding
Po-Chun Chen, Ta-Chung Chi, Shang-Yu Su +1
Spoken language understanding (SLU) is an essential component in conversational systems. Most SLU component treats each utterance independently, and then the following components a…
Speaker Role Contextual Modeling for Language Understanding and Dialogue Policy Learning
Ta-Chung Chi, Po-Chun Chen, Shang-Yu Su +1
Language understanding (LU) and dialogue policy learning are two essential components in conversational systems. Human-human dialogues are not well-controlled and often random and…
Order-Preserving Abstractive Summarization for Spoken Content Based on Connectionist Temporal Classification
Bo-Ru Lu, Frank Shyu, Yun-Nung Chen +2
Connectionist temporal classification (CTC) is a powerful approach for sequence-to-sequence learning, and has been popularly used in speech recognition. The central ideas of CTC in…
MUSE: Modularizing Unsupervised Sense Embeddings
Guang-He Lee, Yun-Nung Chen
This paper proposes to address the word sense ambiguity issue in an unsupervised manner, where word sense representations are learned along a word sense selection mechanism given c…
Investigation of Language Understanding Impact for Reinforcement Learning Based Dialogue Systems
Xiujun Li, Yun-Nung Chen, Lihong Li +2
Language understanding is a key component in a spoken dialogue system. In this paper, we investigate how the language understanding module influences the dialogue system performanc…
End-to-End Task-Completion Neural Dialogue Systems
Xiujun Li, Yun-Nung Chen, Lihong Li +2
One of the major drawbacks of modularized task-completion dialogue systems is that each module is trained individually, which presents several challenges. For example, downstream m…
End-to-End Joint Learning of Natural Language Understanding and Dialogue Manager
Xuesong Yang, Yun-Nung Chen, Dilek Hakkani-Tur +4
Natural language understanding and dialogue policy learning are both essential in conversational systems that predict the next system actions in response to a current user utteranc…