Embodiment and American Sign Language
Exploring sensory-motor influences in the recognition of American Sign Language
Bibliographic Data
| ID | 12824469 |
|---|---|
| Authors | David P Corina (0000-0003-1832-9966, University of California, Davis, corresponding author), Eva Gutiérrez (0000-0002-6569-2138, Universitat de València) |
| Year | 2016 |
| Volume | 15 |
| Issue | 3 |
| Pages | 291-305 |
| Publication date | 2016-11-28 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Gesture (JOURNAL) |
| Journal identifiers | ISSN: 1568-1475 • E-ISSN: 1569-9773 |
| Publisher | John Benjamins Publishing Company (PUBLISHER • NL) |
| DOI | 10.1075/gest.15.3.01cor |
| OpenAlex | W2558492977 |
| Language | EN |
| Citations received | 3 |
| References cited | 28 |
Little is known about how individual signs that occur in naturally produced signed languages are recognized. Here we examine whether sign understanding may be grounded in sensorimotor properties by evaluating a signer’s ability to make lexical decisions to American Sign Language (ASL) signs that are articulated either congruent with or incongruent with the observer’s own handedness. Our results show little evidence for handedness congruency effects for native signers’ perception of ASL, however handedness congruency effects were seen in non-native late learners of ASL and hearing ASL-English bilinguals. The data are compatible with a theory of sign recognition that makes reference to internally simulated articulatory control signals — a forward model based upon sensory-motor properties of one’s owns body. The data suggest that sign recognition may rely upon an internal body schema when processing is non-optimal as a result of having learned ASL later in life. Native signers however may have developed representations of signs which are less bound to the hand with which it is performed, suggesting a different engagement of an internal forward model for rapid lexical decisions
American Sign Language · Cognitive psychology · Linguistics · Perception · Schema (genetic algorithms · Sign (mathematics · Sign language · Computer Science · Hand Gesture Recognition Systems · Hearing Impairment and Communication · Language, Metaphor, and Cognition · Psychology
| Unique citing works | 3 |
|---|---|
| Citations per year | 0.43 |
| Citation span | 2019 - 2024 (6) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |