Invention Grant
- Patent Title: Generating ground truth annotations corresponding to digital image editing dialogues for training state tracking models
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Application No.: US16366904Application Date: 2019-03-27
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Publication No.: US11100917B2Publication Date: 2021-08-24
- Inventor: Trung Bui , Zahra Rahimi , Yinglan Ma , Seokhwan Kim , Franck Dernoncourt
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Keller Jolley Preece
- Main IPC: G10L15/06
- IPC: G10L15/06 ; G06F3/16 ; G06F3/0482 ; G06N20/00 ; G10L15/22 ; G10L15/18 ; G06F3/0484 ; G06F40/169

Abstract:
The present disclosure relates to systems, non-transitory computer-readable media, and methods that generate ground truth annotations of target utterances in digital image editing dialogues in order to create a state-driven training data set. In particular, in one or more embodiments, the disclosed systems utilize machine and user defined tags, machine learning model predictions, and user input to generate a ground truth annotation that includes frame information in addition to intent, attribute, object, and/or location information. In at least one embodiment, the disclosed systems generate ground truth annotations in conformance with an annotation ontology that results in fast and accurate digital image editing dialogue annotation.
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