ConvLab: Multi-Domain End-to-End Dialog System Platform
This provides a tool for researchers in dialog systems to streamline experimentation, but it is incremental as it builds on existing datasets and methods.
The authors introduced ConvLab, an open-source platform for multi-domain end-to-end dialog systems, enabling researchers to quickly set up experiments and compare various approaches using annotated datasets and pre-trained models, as demonstrated by extending the MultiWOZ dataset with user dialog act annotations.
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.