Published on Fri Oct 09 2020 MEEP: An Open-Source Platform for Human-Human Dialog Collection and
End-to-End Agent Training Posts Similar Sun Sep 01 2019 Artificial Intelligence Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset The initial release of the Taskmaster-1 dataset includes 13,215 task-based dialogs. The dataset will evoke interest in written vs. spoken language, discourse patterns, error handling and other phenomena related to dialog system research, development and design. Tue Dec 29 2020 Artificial Intelligence RADDLE: An Evaluation Benchmark and Analysis Platform for Robust
Task-oriented Dialog Systems TicketTalk: Toward human-level performance with end-to-end,
transaction-based dialog systems The researchers used TicketTalk, a movie ticketing dialog dataset with 23,789 annotated conversations. In qualitative human evaluations, model-generated responses trained on just 10,000 TicketTalk dialogs were rated to "make sense" 86.5 percent of the time, almost the same as human responses in the same contexts. Mon Jan 15 2018 Artificial Intelligence Building a Conversational Agent Overnight with Dialogue Self-Play We propose Machines Talking To Machines (M2M), a framework combining automation and crowdsourcing to rapidly bootstrap end-to-end dialogue agents. M2M scales to new tasks with just a task schema and an API client from the dialogue system developer. Sun Jul 29 2018 Artificial Intelligence Microsoft Dialogue Challenge: Building End-to-End Task-Completion
Dialogue Systems Dialogue Challenge for building end-to-end task-completion dialogue systems. We will release human-annotated conversational data in three domains (movie-ticket booking, restaurant reservation, and taxi booking) The final submitted systems will be evaluated both in simulated setting and by judges. Mon Feb 08 2021 Artificial Intelligence A Hybrid Task-Oriented Dialog System with Domain and Task Adaptive
Pretraining This paper describes our submission for the End-to-end Multi-domain Task Completed Dialog shared task at the 9th Dialog System Technology Challenge. We make our source code publicly available. Our proposed method significantly outperforms baselines and ties for first place in official evaluation.