ConvLab: Multi-Domain End-to-End Dialog System Platform - Lee, Sungjin; Zhu, Qi; Takanobu, Ryuichi; Zhang, Zheng; Zhang, Yaoqin; Li, Xiang; Li, Jinchao; Peng, Baolin; Li, Xiujun; Huang, Minlie; Gao, Jianfeng (Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 2019)
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.