Seonghan Ryu
2018
Out-of-domain Detection based on Generative Adversarial Network
Seonghan Ryu
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Sangjun Koo
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Hwanjo Yu
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Gary Geunbae Lee
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
The main goal of this paper is to develop out-of-domain (OOD) detection for dialog systems. We propose to use only in-domain (IND) sentences to build a generative adversarial network (GAN) of which the discriminator generates low scores for OOD sentences. To improve basic GANs, we apply feature matching loss in the discriminator, use domain-category analysis as an additional task in the discriminator, and remove the biases in the generator. Thereby, we reduce the huge effort of collecting OOD sentences for training OOD detection. For evaluation, we experimented OOD detection on a multi-domain dialog system. The experimental results showed the proposed method was most accurate compared to the existing methods.
2015
Exploiting knowledge base to generate responses for natural language dialog listening agents
Sangdo Han
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Jeesoo Bang
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Seonghan Ryu
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Gary Geunbae Lee
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue
2012
A Hierarchical Domain Model-Based Multi-Domain Selection Framework for Multi-Domain Dialog Systems
Seonghan Ryu
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Donghyeon Lee
|
Injae Lee
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Sangdo Han
|
Gary Geunbae Lee
|
Myungjae Kim
|
Kyungduk Kim
Proceedings of COLING 2012: Posters
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Co-authors
- Gary Geunbae Lee 3
- Sangdo Han 2
- Sangjun Koo 1
- Hwanjo Yu 1
- Jeesoo Bang 1
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