ConvLab: Multi-Domain End-to-End Dialog System Platform
Sungjin Lee, Qi Zhu, Ryuichi Takanobu, Zheng Zhang, Yaoqin Zhang, Xiang Li, Jinchao Li, Baolin Peng, Xiujun Li, Minlie Huang, Jianfeng Gao
Abstract
We present ConvLab, an open-source multi-domain end-to-end dialog system platform, that enables researchers to quickly set up experiments with reusable components and compare a large set of different approaches, ranging from conventional pipeline systems to end-to-end neural models, in common environments. ConvLab offers a set of fully annotated datasets and associated pre-trained reference models. As a showcase, we extend the MultiWOZ dataset with user dialog act annotations to train all component models and demonstrate how ConvLab makes it easy and effortless to conduct complicated experiments in multi-domain end-to-end dialog settings.- Anthology ID:
- P19-3011
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Marta R. Costa-jussà, Enrique Alfonseca
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 64–69
- Language:
- URL:
- https://aclanthology.org/P19-3011
- DOI:
- 10.18653/v1/P19-3011
- Cite (ACL):
- Sungjin Lee, Qi Zhu, Ryuichi Takanobu, Zheng Zhang, Yaoqin Zhang, Xiang Li, Jinchao Li, Baolin Peng, Xiujun Li, Minlie Huang, and Jianfeng Gao. 2019. ConvLab: Multi-Domain End-to-End Dialog System Platform. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 64–69, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- ConvLab: Multi-Domain End-to-End Dialog System Platform (Lee et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/P19-3011.pdf
- Code
- budzianowski/multiwoz + additional community code
- Data
- MultiWOZ