Conference proceeding
A User-Powered American Sign Language Dictionary
Proceedings of the 18th ACM Conference on computer supported cooperative work & social computing, pp.1837-1848
CSCW '15
02/28/2015
DOI: 10.1145/2675133.2675226
Abstract
Students learning American Sign Language (ASL) have trouble searching for the meaning of unfamiliar signs. ASL signs can be differentiated by a small set of simple features including hand shape, orientation, location, and movement. In a feature-based ASL-to-English dictionary, users search for a sign by providing a query, which is a set of observed features. Because there is natural variability in the way signs are executed, and observations are error-prone, an approach other than exact matching of features is needed. We propose ASL-Search, an ASL-to-English dictionary entirely powered by its users. ASL-Search utilizes Latent Semantic Analysis (LSA) on a database of feature-based user queries to account for variability. To demonstrate ASL-Search's viability, we created ASL-Flash, a learning tool that presents online flashcards to ASL students and provides query data. Our simulations on this data serve as a proof of concept, demonstrating that our dictionary's performance improves with use and performs well for users with varied levels of ASL experience.
Details
- Title: Subtitle
- A User-Powered American Sign Language Dictionary
- Creators
- Danielle Bragg - University of WashingtonKyle Rector - University of WashingtonRichard Ladner - University of Washington
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the 18th ACM Conference on computer supported cooperative work & social computing, pp.1837-1848
- Series
- CSCW '15
- DOI
- 10.1145/2675133.2675226
- Publisher
- ACM
- Grant note
- DOI: 10.13039/501100004608, name: National Science Foundation, award: 0915268
- Language
- English
- Date published
- 02/28/2015
- Academic Unit
- Computer Science
- Record Identifier
- 9984259420902771
Metrics
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