DialEdit: Annotations for Spoken Conversational Image Editing
Abstract
We present a spoken dialogue corpus and annotation scheme for conversational image editing, where people edit an image interactively through spoken language instructions. Our corpus contains spoken conversations between two human participants: users requesting changes to images and experts performing these modifications in real time. Our annotation scheme consists of 26 dialogue act labels covering instructions, requests, and feedback, together with actions and entities for the content of the edit requests. The corpus supports research and development in areas such as incremental intent recognition, visual reference resolution, image-grounded dialogue modeling, dialogue state tracking, and user modeling.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 2018
- Accession Number
- AD1158386
Entities
People
- Jacqueline Brixey
- Kallirroi Georgila
- Ramesh Manuvinakurike
- Ron Artstein
- Trung Bui
- Walter Chang
Organizations
- Adobe
- University of Southern California