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ConvLab: Multi-Domain End-to-End Dialog System Platform

Authors :
Lee, Sungjin
Zhu, Qi
Takanobu, Ryuichi
Li, Xiang
Zhang, Yaoqin
Zhang, Zheng
Li, Jinchao
Peng, Baolin
Li, Xiujun
Huang, Minlie
Gao, Jianfeng
Publication Year :
2019

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1904.08637
Document Type :
Working Paper