Discriminant features and temporal structure of nonmanuals in American Sign Language.

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 nonman...

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Main Authors: C Fabian Benitez-Quiroz, Kadir Gökgöz, Ronnie B Wilbur, Aleix M Martinez
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3916328?pdf=render
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spelling doaj-cea3919335034f9b9078cf4dacb474f02020-11-24T21:35:12ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0192e8626810.1371/journal.pone.0086268Discriminant features and temporal structure of nonmanuals in American Sign Language.C Fabian Benitez-QuirozKadir GökgözRonnie B WilburAleix M MartinezTo 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.http://europepmc.org/articles/PMC3916328?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author C Fabian Benitez-Quiroz
Kadir Gökgöz
Ronnie B Wilbur
Aleix M Martinez
spellingShingle C Fabian Benitez-Quiroz
Kadir Gökgöz
Ronnie B Wilbur
Aleix M Martinez
Discriminant features and temporal structure of nonmanuals in American Sign Language.
PLoS ONE
author_facet C Fabian Benitez-Quiroz
Kadir Gökgöz
Ronnie B Wilbur
Aleix M Martinez
author_sort C Fabian Benitez-Quiroz
title Discriminant features and temporal structure of nonmanuals in American Sign Language.
title_short Discriminant features and temporal structure of nonmanuals in American Sign Language.
title_full Discriminant features and temporal structure of nonmanuals in American Sign Language.
title_fullStr Discriminant features and temporal structure of nonmanuals in American Sign Language.
title_full_unstemmed Discriminant features and temporal structure of nonmanuals in American Sign Language.
title_sort discriminant features and temporal structure of nonmanuals in american sign language.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description 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.
url http://europepmc.org/articles/PMC3916328?pdf=render
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