Sangjun Koo


2018

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Out-of-domain Detection based on Generative Adversarial Network
Seonghan Ryu | Sangjun Koo | Hwanjo Yu | 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

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Conversational Knowledge Teaching Agent that uses a Knowledge Base
Kyusong Lee | Paul Hongsuck Seo | Junhwi Choi | Sangjun Koo | Gary Geunbae Lee
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue