MEEP: An Open-Source Platform for Human-Human Dialog Collection and End-to-End Agent Training
Arkady Arkhangorodsky, Amittai Axelrod, Christopher Chu, Scot Fang,, Yiqi Huang, Ajay Nagesh, Xing Shi, Boliang Zhang, Kevin Knight

TL;DR
MEEP is an open-source platform designed for collecting human-human dialog data and training end-to-end task-oriented dialog agents within a flexible, push-button environment, demonstrated through a trip destination assistant.
Contribution
It introduces a novel dialog platform that combines data collection and agent training with flexible utterance and API call capabilities.
Findings
Successful collection of human-human dialog corpora.
Effective training of end-to-end dialog agents.
Demonstration of a trip destination assistant application.
Abstract
We create a new task-oriented dialog platform (MEEP) where agents are given considerable freedom in terms of utterances and API calls, but are constrained to work within a push-button environment. We include facilities for collecting human-human dialog corpora, and for training automatic agents in an end-to-end fashion. We demonstrate MEEP with a dialog assistant that lets users specify trip destinations.
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Speech and dialogue systems
