From Text to Pictures

eagle-i ID

Resource Type

Properties

1. Related grant number

   NSF Award Abstract #0904361

2. Resource Description

   This software implements new theoretical models and technology to automatically convert descriptive text into 3D scenes representing the text's meaning. They do this via the Scenario-Based Lexical Knowledge Resource (SBLR), a resource they are creating from existing sources (PropBank, WordNet, FrameNet) and from automated mining of Wikipedia and other un-annotated text. In addition to predicate-argument structure and semantic roles, the SBLR includes necessary roles, typical role fillers, contextual elements, and activity poses which enables analysis of input sentences at a deep level and assembly of appropriate elements from libraries of 3D objects to depict the fuller scene implied by a sentence. For example, "Terry ate breakfast" does not tell us where (kitchen, dining room, restaurant) or what he ate (cereal, doughnut, or rice, umeboshi, and natto). These elements must be supplied from knowledge about typical role fillers appropriate for the information that is specified in the input. Note that the SBLR has a component that varies by cultural context.

3. Used by

   Center for Spoken Language Understanding

4. Website(s)

   http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0904361

5. Website(s)

   http://www.ohsu.edu/xd/education/schools/school-of-medicine/departments/basic-science-departments/biomedical-engineering/center-for-spoken-language-understanding/from-text-to-pictures.cfm?WT_rank=1

6. Related Technique

   Computational modeling technique

7. Developed by

   0000012b-36a0-fcf3-62b8-f47280000000

8. Software license

   Open source software license