Doc2Dial: A Framework for Dialogue Composition Grounded in Documents

We introduce DOC2DIAL, an end-to-end framework for generating conversational data grounded in given documents. It takes the documents as input and generates the pipelined tasks for obtaining the annotations specifically for producing the simulated dialog flows. Then, the dialog flows are used to guide the collection of the utterances via the integrated crowdsourcing tool. The outcomes include the human-human dialogue data grounded in the given documents, as well as various types of automatically or human labeled annotations that help ensure the quality of the dialog data with the flexibility to (re)composite dialogues. We expect such data can facilitate building automated dialogue agents for goal-oriented tasks. We demonstrate DOC2DIAL system with the various domain documents for customer care.

Authors

• Song Feng AWS AI Labs
• Kshitij Fadnis
• Q. Vera Liao
• Luis A. Lastras

Keywords

No keywords are indexed for this paper.