ERIC Number: EJ1387118
Record Type: Journal
Publication Date: 2022
Pages: 29
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0302-1475
EISSN: EISSN-1533-6263
Assessing an Automated Tool to Quantify Variation in Movement and Location: A Case Study of American Sign Language and Ghanaian Sign Language
Fragkiadakis, Manolis
Sign Language Studies, v23 n1 p98-126 Fall 2022
Signs in sign languages have been mainly analyzed as composed of three formational elements: hand configuration, location, and movement. Researchers compare and contrast lexical differences and similarities among different signs and languages based on these formal elements. Such measurement requires extensive manual annotation of each feature based on a predefined process and can be time consuming because it is based on abstract representations that usually do not take into account the individual traits of different signers. This study showcases a newly developed tool named DistSign, used here to measure and visualize variation based on the wrist trajectory in the lexica of two sign languages, namely American Sign Language (ASL) and Ghanaian Sign Language (GSL), which are assumed to be historically related (Edward 2014). The tool utilizes the pretrained pose estimation framework OpenPose to track the body joints of different signers. Subsequently, the Dynamic Time Warping (DTW) algorithm, which measures the similarity between two temporal sequences, is used to quantify variation in the paths of the dominant hand's wrist across signs. This enables one to efficiently identify cognates across languages, as well as false cognates. The results show that the DistSign tool can recognize cognates with a 60 percent accuracy, using a semiautomated method that utilizes the Levenshtein distance metric as a baseline.
Descriptors: American Sign Language, Sign Language, Contrastive Linguistics, Foreign Countries, Language Variation, Computer Software, Guidelines, Algorithms, Semantics, Handedness, Human Body, Visual Aids, Psychomotor Skills
Gallaudet University Press. 800 Florida Avenue NE, Denison House, Washington, DC 20002-3695. Tel: 202-651-5488; Fax: 202-651-5489; Web site: http://gupress.gallaudet.edu/SLS.html
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Ghana
Grant or Contract Numbers: N/A