Context-Sensitive Generation of Open-Domain Conversational Responses
Weinan Zhang, Yiming Cui, Yifa Wang, Qingfu Zhu, Lingzhi Li, Lianqiang Zhou, Ting Liu
Abstract
Despite the success of existing works on single-turn conversation generation, taking the coherence in consideration, human conversing is actually a context-sensitive process. Inspired by the existing studies, this paper proposed the static and dynamic attention based approaches for context-sensitive generation of open-domain conversational responses. Experimental results on two public datasets show that the proposed static attention based approach outperforms all the baselines on automatic and human evaluation.- Anthology ID:
- C18-1206
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2437–2447
- Language:
- URL:
- https://aclanthology.org/C18-1206
- DOI:
- Cite (ACL):
- Weinan Zhang, Yiming Cui, Yifa Wang, Qingfu Zhu, Lingzhi Li, Lianqiang Zhou, and Ting Liu. 2018. Context-Sensitive Generation of Open-Domain Conversational Responses. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2437–2447, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- Context-Sensitive Generation of Open-Domain Conversational Responses (Zhang et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/C18-1206.pdf