scholarly journals Exploring Networks of Lexical Variation in Russian Sign Language

2022 ◽  
Vol 12 ◽  
Author(s):  
Vadim Kimmelman ◽  
Anna Komarova ◽  
Lyudmila Luchkova ◽  
Valeria Vinogradova ◽  
Oksana Alekseeva
Keyword(s):  
Sign Language ◽  
Visualization Tool ◽  
Sign Languages ◽  
Color Terms ◽  
Lexical Variation ◽  
Orientation Movement ◽  
Complex Cases ◽  
Formal Rules

When describing variation at the lexical level in sign languages, researchers often distinguish between phonological and lexical variants, using the following principle: if two signs differ in only one of the major phonological components (handshape, orientation, movement, location), then they are considered phonological variants, otherwise they are considered separate lexemes. We demonstrate that this principle leads to contradictions in some simple and more complex cases of variation. We argue that it is useful to visualize the relations between variants as graphs, and we describe possible networks of variants that can arise using this visualization tool. We further demonstrate that these scenarios in fact arise in the case of variation in color terms and kinship terms in Russian Sign Language (RSL), using a newly created database of lexical variation in RSL. We show that it is possible to develop a set of formal rules that can help distinguish phonological and lexical variation also in the problematic scenarios. However, we argue that it might be a mistake to dismiss the actual patterns of variant relations in order to arrive at the binary lexical vs. phonological variant opposition.

The effect of sociolinguistic factors on variation in the Kata Kolok lexicon

2020 ◽  
Vol 6 (1) ◽  
pp. 53-88
Author(s):  
Katie Mudd ◽  
Hannah Lutzenberger ◽  
Connie de Vos ◽  
Paula Fikkert ◽  
Onno Crasborn ◽  
...  
Keyword(s):  
Family Member ◽  
Sign Language ◽  
Preliminary Evidence ◽  
Deaf Community ◽  
Sign Languages ◽  
Lexical Variation ◽  
Supplementary Material ◽  
Picture Description ◽  
Description Task

Abstract Abstract (International Sign) Sign languages can be categorized as shared sign languages or deaf community sign languages, depending on the context in which they emerge. It has been suggested that shared sign languages exhibit more variation in the expression of everyday concepts than deaf community sign languages (Meir, Israel, Sandler, Padden, & Aronoff, 2012). For deaf community sign languages, it has been shown that various sociolinguistic factors condition this variation. This study presents one of the first in-depth investigations of how sociolinguistic factors (deaf status, age, clan, gender and having a deaf family member) affect lexical variation in a shared sign language, using a picture description task in Kata Kolok. To study lexical variation in Kata Kolok, two methodologies are devised: the identification of signs by underlying iconic motivation and mapping, and a way to compare individual repertoires of signs by calculating the lexical distances between participants. Alongside presenting novel methodologies to study this type of sign language, we present preliminary evidence of sociolinguistic factors that may influence variation in the Kata Kolok lexicon.

Fonologische Beschrijving Van Gebaren En Psychomotorisch Onderzoek

1986 ◽  
Vol 24 ◽  
pp. 100-110
Author(s):  
F· Loncke
Keyword(s):  
Sign Language ◽  
Mentally Retarded ◽  
Deaf Children ◽  
Sign Languages ◽  
Language Programs ◽  
Place Of Articulation ◽  
Orientation Movement ◽  
In The Beginning ◽  
Further Development ◽  
Expressive Strategies

In the beginning of the 60s, people realized that the signs of sign languages could be described as a simultaneous bundle of phonemes (place of articulation, handconfiguration, orientation, movement). This proved to be inspiring for the further development of sign language linguistics. Moreover, this phonemic description correlates with psychological, perceptual and expressive strategies in native users. In young deaf children who acquire a sign language, we see an early development of phonological awareness. This specific aware-ness might be linked to the kinesiologicai and psychomotor status of the sign language articulators. It could be exploited in bilingual (sign language/ spoken language) programs for educating deaf children. The introduction of sign systems rather than sign language in communication with other populations (severely mentally retarded, autistic) still leaves the question open whether the learning of signs mirrors the learning of its phonemes. Proposals for analyzing sign phonemes can be used to test this. Our data are based on an imitation and a memory test with nonverbal, severely mentally retarded persons. They point in the direction of a hier-archical gradual mastery of 'psychomotor' features of the handshape.

Crosslinguistic similarity and variation in the simultaneous morphology of sign languages

2020 ◽  
Vol 37 (4) ◽  
pp. 571-608
Author(s):  
Diane Brentari ◽  
Laura Horton ◽  
Susan Goldin-Meadow
Keyword(s):  
American Sign Language ◽  
Sign Language ◽  
Optimality Theory ◽  
Sign Languages ◽  
British Sign Language ◽  
Verb Phrases ◽  
Classifier Predicates ◽  
Crosslinguistic Variation ◽  
Hong Kong Sign Language ◽  
British Sign

Abstract Two differences between signed and spoken languages that have been widely discussed in the literature are: the degree to which morphology is expressed simultaneously (rather than sequentially), and the degree to which iconicity is used, particularly in predicates of motion and location, often referred to as classifier predicates. In this paper we analyze a set of properties marking agency and number in four sign languages for their crosslinguistic similarities and differences regarding simultaneity and iconicity. Data from American Sign Language (ASL), Italian Sign Language (LIS), British Sign Language (BSL), and Hong Kong Sign Language (HKSL) are analyzed. We find that iconic, cognitive, phonological, and morphological factors contribute to the distribution of these properties. We conduct two analyses—one of verbs and one of verb phrases. The analysis of classifier verbs shows that, as expected, all four languages exhibit many common formal and iconic properties in the expression of agency and number. The analysis of classifier verb phrases (VPs)—particularly, multiple-verb predicates—reveals (a) that it is grammatical in all four languages to express agency and number within a single verb, but also (b) that there is crosslinguistic variation in expressing agency and number across the four languages. We argue that this variation is motivated by how each language prioritizes, or ranks, several constraints. The rankings can be captured in Optimality Theory. Some constraints in this account, such as a constraint to be redundant, are found in all information systems and might be considered non-linguistic; however, the variation in constraint ranking in verb phrases reveals the grammatical and arbitrary nature of linguistic systems.

scholarly journals Interpretation of Swedish Sign Language Using Convolutional Neural Networks and Transfer Learning

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Gustaf Halvardsson ◽  
Johanna Peterson ◽  
César Soto-Valero ◽  
Benoit Baudry
Keyword(s):  
Neural Networks ◽  
Sign Language ◽  
Transfer Learning ◽  
Convolutional Neural Networks ◽  
Web Application ◽  
Training Dataset ◽  
Motion Processing ◽  
Image Perception ◽  
Sign Languages ◽  
High Level

AbstractThe automatic interpretation of sign languages is a challenging task, as it requires the usage of high-level vision and high-level motion processing systems for providing accurate image perception. In this paper, we use Convolutional Neural Networks (CNNs) and transfer learning to make computers able to interpret signs of the Swedish Sign Language (SSL) hand alphabet. Our model consists of the implementation of a pre-trained InceptionV3 network, and the usage of the mini-batch gradient descent optimization algorithm. We rely on transfer learning during the pre-training of the model and its data. The final accuracy of the model, based on 8 study subjects and 9400 images, is 85%. Our results indicate that the usage of CNNs is a promising approach to interpret sign languages, and transfer learning can be used to achieve high testing accuracy despite using a small training dataset. Furthermore, we describe the implementation details of our model to interpret signs as a user-friendly web application.

scholarly journals Computer-assisted sign language translation: a study of translators’ practice to specify CAT software

2021 ◽  
Author(s):  
Marion Kaczmarek ◽  
Michael Filhol
Keyword(s):  
Sign Language ◽  
Language Translation ◽  
Computer Assisted ◽  
Translation Process ◽  
Sign Languages ◽  
Subjective Data ◽  
Do So

AbstractProfessional Sign Language translators, unlike their text-to-text counterparts, are not equipped with computer-assisted translation (CAT) software. Those softwares are meant to ease the translators’ tasks. No prior study as been conducted on this topic, and we aim at specifying such a software. To do so, we based our study on the professional Sign Language translators’ practices and needs. The aim of this paper is to identify the necessary steps in the text-to-sign translation process. By filming and interviewing professionals for both objective and subjective data, we build a list of tasks and see if they are systematic and performed in a definite order. Finally, we reflect on how CAT tools could assist those tasks, how to adapt the existing tools to Sign Language and what is necessary to add in order to fit the needs of Sign Language translation. In the long term, we plan to develop a first prototype of CAT software for sign languages.

The FATE Landscape of Sign Language AI Datasets

2021 ◽  
Vol 14 (2) ◽  
pp. 1-45
Author(s):  
Danielle Bragg ◽  
Naomi Caselli ◽  
Julie A. Hochgesang ◽  
Matt Huenerfauth ◽  
Leah Katz-Hernandez ◽  
...  
Keyword(s):  
Sign Language ◽  
New Technology ◽  
Individual Data ◽  
Community Members ◽  
Sign Languages ◽  
Language Data ◽  
History Of ◽  
Language Technologies ◽  
And Storage ◽  
Access Mechanisms

Sign language datasets are essential to developing many sign language technologies. In particular, datasets are required for training artificial intelligence (AI) and machine learning (ML) systems. Though the idea of using AI/ML for sign languages is not new, technology has now advanced to a point where developing such sign language technologies is becoming increasingly tractable. This critical juncture provides an opportunity to be thoughtful about an array of Fairness, Accountability, Transparency, and Ethics (FATE) considerations. Sign language datasets typically contain recordings of people signing, which is highly personal. The rights and responsibilities of the parties involved in data collection and storage are also complex and involve individual data contributors, data collectors or owners, and data users who may interact through a variety of exchange and access mechanisms. Deaf community members (and signers, more generally) are also central stakeholders in any end applications of sign language data. The centrality of sign language to deaf culture identity, coupled with a history of oppression, makes usage by technologists particularly sensitive. This piece presents many of these issues that characterize working with sign language AI datasets, based on the authors’ experiences living, working, and studying in this space.

People Are Less Susceptible to Illusion When They Use Their Hands to Communicate Rather Than Estimate

2021 ◽  
pp. 095679762199155
Author(s):  
Amanda R. Brown ◽  
Wim Pouw ◽  
Diane Brentari ◽  
Susan Goldin-Meadow
Keyword(s):  
American Sign Language ◽  
Sign Language ◽  
English Speakers ◽  
American Sign ◽  
Estimation Task ◽  
Sign Languages ◽  
Lyer Illusion ◽  
Description Task ◽  
The Way

When we use our hands to estimate the length of a stick in the Müller-Lyer illusion, we are highly susceptible to the illusion. But when we prepare to act on sticks under the same conditions, we are significantly less susceptible. Here, we asked whether people are susceptible to illusion when they use their hands not to act on objects but to describe them in spontaneous co-speech gestures or conventional sign languages of the deaf. Thirty-two English speakers and 13 American Sign Language signers used their hands to act on, estimate the length of, and describe sticks eliciting the Müller-Lyer illusion. For both gesture and sign, the magnitude of illusion in the description task was smaller than the magnitude of illusion in the estimation task and not different from the magnitude of illusion in the action task. The mechanisms responsible for producing gesture in speech and sign thus appear to operate not on percepts involved in estimation but on percepts derived from the way we act on objects.

scholarly journals Transitivity prominence within and across modalities

2019 ◽  
Vol 5 (1) ◽  
pp. 666-689
Author(s):  
Carl Börstell ◽  
Tommi Jantunen ◽  
Vadim Kimmelman ◽  
Vanja de Lint ◽  
Johanna Mesch ◽  
...  
Keyword(s):  
Sign Language ◽  
Sign Languages ◽  
Corpus Data ◽  
Direct Objects ◽  
Positive Correlations ◽  
Verb Meaning

AbstractWe investigate transitivity prominence of verbs across signed and spoken languages, based on data from both valency dictionaries and corpora. Our methodology relies on the assumption that dictionary data and corpus-based measures of transitivity are comparable, and we find evidence in support of this through the direct comparison of these two types of data across several spoken languages. For the signed modality, we measure the transitivity prominence of verbs in five sign languages based on corpus data and compare the results to the transitivity prominence hierarchy for spoken languages reported in Haspelmath (2015). For each sign language, we create a hierarchy for 12 verb meanings based on the proportion of overt direct objects per verb meaning. We use these hierarchies to calculate correlations between languages – both signed and spoken – and find positive correlations between transitivity hierarchies. Additional findings of this study include the observation that locative arguments seem to behave differently than direct objects judging by our measures of transitivity, and that relatedness among sign languages does not straightforwardly imply similarity in transitivity hierarchies. We conclude that our findings provide support for a modality-independent, semantic basis of transitivity.

The Medium and the Message

1999 ◽  
Vol 2 (2) ◽  
pp. 187-215 ◽  
Author(s):  
Wendy Sandler
Keyword(s):  
Facial Expression ◽  
Sign Language ◽  
Spoken Language ◽  
Sign Languages ◽  
Prosodic Word ◽  
Special Stress ◽  
New Perspective ◽  
New Evidence ◽  
Phonological Phrase ◽  
The Relationship

In natural communication, the medium through which language is transmitted plays an important and systematic role. Sentences are broken up rhythmically into chunks; certain elements receive special stress; and, in spoken language, intonational tunes are superimposed onto these chunks in particular ways — all resulting in an intricate system of prosody. Investigations of prosody in Israeli Sign Language demonstrate that sign languages have comparable prosodic systems to those of spoken languages, although the phonetic medium is completely different. Evidence for the prosodic word and for the phonological phrase in ISL is examined here within the context of the relationship between the medium and the message. New evidence is offered to support the claim that facial expression in sign languages corresponds to intonation in spoken languages, and the term “superarticulation” is coined to describe this system in sign languages. Interesting formaldiffer ences between the intonationaltunes of spoken language and the “superarticulatory arrays” of sign language are shown to offer a new perspective on the relation between the phonetic basis of language, its phonological organization, and its communicative content.

scholarly journals Monitoring Different Phonological Parameters of Sign Language Engages the Same Cortical Language Network but Distinctive Perceptual Ones

2016 ◽  
Vol 28 (1) ◽  
pp. 20-40 ◽  
Author(s):  
Velia Cardin ◽  
Eleni Orfanidou ◽  
Lena Kästner ◽  
Jerker Rönnberg ◽  
Bencie Woll ◽  
...  
Keyword(s):  
Sign Language ◽  
Action Observation ◽  
Sign Languages ◽  
Signed Languages ◽  
Phonological Structure ◽  
British Sign Language ◽  
Action Observation Network ◽  
Native Signers ◽  
British Sign ◽  
Phonological Rules

The study of signed languages allows the dissociation of sensorimotor and cognitive neural components of the language signal. Here we investigated the neurocognitive processes underlying the monitoring of two phonological parameters of sign languages: handshape and location. Our goal was to determine if brain regions processing sensorimotor characteristics of different phonological parameters of sign languages were also involved in phonological processing, with their activity being modulated by the linguistic content of manual actions. We conducted an fMRI experiment using manual actions varying in phonological structure and semantics: (1) signs of a familiar sign language (British Sign Language), (2) signs of an unfamiliar sign language (Swedish Sign Language), and (3) invented nonsigns that violate the phonological rules of British Sign Language and Swedish Sign Language or consist of nonoccurring combinations of phonological parameters. Three groups of participants were tested: deaf native signers, deaf nonsigners, and hearing nonsigners. Results show that the linguistic processing of different phonological parameters of sign language is independent of the sensorimotor characteristics of the language signal. Handshape and location were processed by different perceptual and task-related brain networks but recruited the same language areas. The semantic content of the stimuli did not influence this process, but phonological structure did, with nonsigns being associated with longer RTs and stronger activations in an action observation network in all participants and in the supramarginal gyrus exclusively in deaf signers. These results suggest higher processing demands for stimuli that contravene the phonological rules of a signed language, independently of previous knowledge of signed languages. We suggest that the phonological characteristics of a language may arise as a consequence of more efficient neural processing for its perception and production.

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