Microsoft Dialogue Challenge: Building End-to-End Task-Completion Dialogue Systems

July 29, 2018 · Entered Twilight · 🏛 arXiv.org

"No code URL or promise found in abstract"
"Code repo scraped from project page (backfill)"

Evidence collected by the PWNC Scanner

Repo contents: .gitignore, Human Dialogue Dataset License Terms.txt, README.md, SLT 2018 - MS Dialogue Challenge - CFP.pdf, SubmissionSample, _config.yml, board, cmd.md, data, microsoft-dialogue-challenge-slt2018.pdf, slides, system

Authors Xiujun Li, Yu Wang, Siqi Sun, Sarah Panda, Jingjing Liu, Jianfeng Gao arXiv ID 1807.11125 Category cs.CL: Computation & Language Cross-listed cs.AI, cs.LG Citations 107 Venue arXiv.org Repository https://github.com/xiul-msr/e2e_dialog_challenge ⭐ 194 Last Checked 11 days ago

Abstract

This proposal introduces a Dialogue Challenge for building end-to-end task-completion dialogue systems, with the goal of encouraging the dialogue research community to collaborate and benchmark on standard datasets and unified experimental environment. In this special session, we will release human-annotated conversational data in three domains (movie-ticket booking, restaurant reservation, and taxi booking), as well as an experiment platform with built-in simulators in each domain, for training and evaluation purposes. The final submitted systems will be evaluated both in simulated setting and by human judges.