ArticlePloS one2014
Discriminant features and temporal structure of nonmanuals in American Sign Language.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- From Seed to System: The Emergence of Non-Manual Markers for Wh-Questions in Nicaraguan Sign Language.Languages (Basel, Switzerland) · 2022Article
- The promises and perils of automated facial action coding in studying children's emotions.Developmental psychology · 2019Article
- Extricating Manual and Non-Manual Features for Subunit Level Medical Sign Modelling in Automatic Sign Language Classification and Recognition.Journal of medical systems · 2017Article
- Labeled Graph Kernel for Behavior Analysis.IEEE transactions on pattern analysis and machine intelligence · 2016Article
- Article
- Prosody in a communication system developed without a language model.Sign language and linguistics · 2014Article
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4 authors.
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Abstract
To fully define the grammar of American Sign Language (ASL), a linguistic model of its nonmanuals needs to be constructed. While significant progress has been made to understand the features defining ASL manuals, after years of research, much still needs to be done to uncover the discriminant nonmanual components. The major barrier to achieving this goal is the difficulty in correlating facial features and linguistic features, especially since these correlations may be temporally defined. For example, a facial feature (e.g., head moves down) occurring at the end of the movement of another facial feature (e.g., brows moves up), may specify a Hypothetical conditional, but only if this time relationship is maintained. In other instances, the single occurrence of a movement (e.g., brows move up) can be indicative of the same grammatical construction. In the present paper, we introduce a linguistic-computational approach to efficiently carry out this analysis. First, a linguistic model of the face is used to manually annotate a very large set of 2,347 videos of ASL nonmanuals (including tens of thousands of frames). Second, a computational approach is used to determine which features of the linguistic model are more informative of the grammatical rules under study. We used the proposed approach to study five types of sentences--Hypothetical conditionals, Yes/no questions, Wh-questions, Wh-questions postposed, and Assertions--plus their polarities--positive and negative. Our results verify several components of the standard model of ASL nonmanuals and, most importantly, identify several previously unreported features and their temporal relationship. Notably, our results uncovered a complex interaction between head position and mouth shape. These findings define some temporal structures of ASL nonmanuals not previously detected by other approaches.
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