560 citations · 1.1k across the 56 of their papers we have counts for
5 papers · 2 filters
Building Task-Oriented Visual Dialog Systems Through Alternative Optimization Between Dialog Policy and Language Generation
Mingyang Zhou, Josh Arnold, Zhou Yu
Reinforcement learning (RL) is an effective approach to learn an optimal dialog policy for task-oriented visual dialog systems. A common practice is to apply RL on a neural sequenc…
Dependency Parsing for Spoken Dialog Systems
Sam Davidson, Dian Yu, Zhou Yu
Dependency parsing of conversational input can play an important role in language understanding for dialog systems by identifying the relationships between entities extracted from…
How to Build User Simulators to Train RL-based Dialog Systems
Weiyan Shi, Kun Qian, Xuewei Wang +1
User simulators are essential for training reinforcement learning (RL) based dialog models. The performance of the simulator directly impacts the RL policy. However, building a goo…
MIDAS: A Dialog Act Annotation Scheme for Open Domain Human Machine Spoken Conversations
Dian Yu, Zhou Yu
Dialog act prediction is an essential language comprehension task for both dialog system building and discourse analysis. Previous dialog act schemes, such as SWBD-DAMSL, are desig…
Unsupervised Dialog Structure Learning
Weiyan Shi, Tiancheng Zhao, Zhou Yu
Learning a shared dialog structure from a set of task-oriented dialogs is an important challenge in computational linguistics. The learned dialog structure can shed light on how to…