Related papers: Context-Sensitive Generation Network for Handing Unknown Slot Values in Dialogue State Tracking

Context-Sensitive Generation Network for Handing Unknown Slot Values in Dialogue State Tracking

URL: http://arxiv.org/abs/2005.03923v3
Date: Fri, 16 Oct 2020 09:31:38 GMT
Title: Context-Sensitive Generation Network for Handing Unknown Slot Values in Dialogue State Tracking
Authors: Puhai Yang, Heyan Huang, and Xian-Ling Mao
Abstract summary: We propose a novel Context-Sensitive Generation network (CSG) which can facilitate the representation of out-of-vocabulary words. Our proposed method performs better than the state-of-the-art baselines.
Score: 38.96838255645715
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: As a key component in a dialogue system, dialogue state tracking plays an important role. It is very important for dialogue state tracking to deal with the problem of unknown slot values. As far as we known, almost all existing approaches depend on pointer network to solve the unknown slot value problem. These pointer network-based methods usually have a hidden assumption that there is at most one out-of-vocabulary word in an unknown slot value because of the character of a pointer network. However, often, there are multiple out-of-vocabulary words in an unknown slot value, and it makes the existing methods perform bad. To tackle the problem, in this paper, we propose a novel Context-Sensitive Generation network (CSG) which can facilitate the representation of out-of-vocabulary words when generating the unknown slot value. Extensive experiments show that our proposed method performs better than the state-of-the-art baselines.

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