Ran Zhao


2017

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Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders
Tiancheng Zhao | Ran Zhao | Maxine Eskenazi
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

While recent neural encoder-decoder models have shown great promise in modeling open-domain conversations, they often generate dull and generic responses. Unlike past work that has focused on diversifying the output of the decoder from word-level to alleviate this problem, we present a novel framework based on conditional variational autoencoders that capture the discourse-level diversity in the encoder. Our model uses latent variables to learn a distribution over potential conversational intents and generates diverse responses using only greedy decoders. We have further developed a novel variant that is integrated with linguistic prior knowledge for better performance. Finally, the training procedure is improved through introducing a bag-of-word loss. Our proposed models have been validated to generate significantly more diverse responses than baseline approaches and exhibit competence of discourse-level decision-making.

2016

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Socially-Aware Animated Intelligent Personal Assistant Agent
Yoichi Matsuyama | Arjun Bhardwaj | Ran Zhao | Oscar Romeo | Sushma Akoju | Justine Cassell
Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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Automatic Recognition of Conversational Strategies in the Service of a Socially-Aware Dialog System
Ran Zhao | Tanmay Sinha | Alan Black | Justine Cassell
Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2012

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A Robust Shallow Temporal Reasoning System
Ran Zhao | Quang Do | Dan Roth
Proceedings of the Demonstration Session at the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies