Neural Response Generation with Meta-words
Can Xu, Wei Wu, Chongyang Tao, Huang Hu, Matt Schuerman, Ying Wang
Abstract
We present open domain dialogue generation with meta-words. A meta-word is a structured record that describes attributes of a response, and thus allows us to explicitly model the one-to-many relationship within open domain dialogues and perform response generation in an explainable and controllable manner. To incorporate meta-words into generation, we propose a novel goal-tracking memory network that formalizes meta-word expression as a goal in response generation and manages the generation process to achieve the goal with a state memory panel and a state controller. Experimental results from both automatic evaluation and human judgment on two large-scale data sets indicate that our model can significantly outperform state-of-the-art generation models in terms of response relevance, response diversity, and accuracy of meta-word expression.- Anthology ID:
- P19-1538
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 5416–5426
- Language:
- URL:
- https://aclanthology.org/P19-1538
- DOI:
- 10.18653/v1/P19-1538
- Cite (ACL):
- Can Xu, Wei Wu, Chongyang Tao, Huang Hu, Matt Schuerman, and Ying Wang. 2019. Neural Response Generation with Meta-words. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5416–5426, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Neural Response Generation with Meta-words (Xu et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/P19-1538.pdf