scholarly journals Towards a dependency treebank for Spanish Sign Language (LSE)

2020 ◽  
Vol 23 ◽  
pp. 111-143
Author(s):  
José M. García ◽  
Carmen Cabeza
Keyword(s):  
Sign Language ◽  
Syntactic Analysis ◽  
Visual Modality ◽  
Sign Languages ◽  
First Results ◽  
Dependency Syntax

This paper presents the foundations, procedures, tests and first results of a dependency treebank of the Spanish Sign Language (LSE). Dependency syntax offers many advantages over other alternatives for the systematic and exhaustive syntactic analysis of a corpus. Nevertheless, the visual modality that is characteristic of sign languages poses unique challenges for their syntactic analysis, among which the most prominent is the simultaneity of expression: both hands, face and other non-manual components. Taking into account these and other particularities of sign languages, the paper explores the main difficulties faced when one tries to apply some usual categories and relations from the syntactic analysis of spoken and written languages to LSE.

scholarly journals Towards a dependency treebank for Spanish Sign Language (LSE)

2020 ◽  
Vol 22 ◽  
pp. 111-143
Author(s):  
José M. García ◽  
Carmen Cabeza
Keyword(s):  
Sign Language ◽  
Syntactic Analysis ◽  
Visual Modality ◽  
Sign Languages ◽  
First Results ◽  
Dependency Syntax

This paper presents the foundations, procedures, tests and first results of a dependency treebank of the Spanish Sign Language (LSE). Dependency syntax offers many advantages over other alternatives for the systematic and exhaustive syntactic analysis of a corpus. Nevertheless, the visual modality that is characteristic of sign languages poses unique challenges for their syntactic analysis, among which the most prominent is the simultaneity of expression: both hands, face and other non-manual components. Taking into account these and other particularities of sign languages, the paper explores the main difficulties faced when one tries to apply some usual categories and relations from the syntactic analysis of spoken and written languages to LSE.

Markers of epistemic modality and their origins

2020 ◽  
pp. 1-44
Author(s):  
Elisabeth Engberg-Pedersen
Keyword(s):  
Sign Language ◽  
Mental State ◽  
Epistemic Uncertainty ◽  
Epistemic Modality ◽  
Visual Modality ◽  
Sign Languages ◽  
Epistemic Modal ◽  
Modal Particles ◽  
Word Forms ◽  
Japanese Sign Language

Abstract Native deaf signers express epistemic modality by different means: mental-state words, clause-internal particles, signs indicating hypothesis, and nonmanually. The data for this study come from two unrelated sign languages, Danish Sign Language and Japanese Sign Language. In dialogues the signers use both calques of majority-language words and signs that appear to have emerged in the sign languages only. Based on the multifunctionality of some word forms, the origin of the epistemic modal particles may be traced back to tags, interjections, and lexical signs, a route motivated by interaction and also found in unrelated spoken languages. Furthermore, in both sign languages, the first-person pronoun can be used, without a verb, as an epistemic “anchor” of a proposition, a construction that seems specific to languages in the gestural-visual modality. Another modality-specific feature is the possibility of transferring the expression of a marker of epistemic uncertainty from one articulator to another.

The prominence of spoken language elements in a sign language

Linguistics ◽  
2016 ◽  
Vol 54 (6) ◽  
Author(s):  
Richard Bank ◽  
Onno Crasborn ◽  
Roeland van Hout
Keyword(s):  
The Netherlands ◽  
Sign Language ◽  
Spoken Language ◽  
Visual Modality ◽  
Sign Languages ◽  
Level Of Education ◽  
Code Mixing ◽  
Regional Origin ◽  
Manual Signs ◽  
Information Streams

Abstractin sign languages consist of simultaneously articulated manual signs and spoken language words. These “mouthings” (typically silent articulations) have been observed for many different sign languages. The present study aims to investigate the extent of such bimodal code-mixing in sign languages by investigating the frequency of mouthings produced by deaf users of Sign Language of the Netherlands (NGT), their co-occurrence with pointing signs, and whether any differences can be explained by sociolinguistic variables such as regional origin and age of the signer. We investigated over 10,000 mouth actions from 70 signers, and found that the mouth and the hands are equally active during signing. Moreover, around 80 % of all mouth actions are mouthings, while the remaining 20 % are unrelated to Dutch. We found frequency differences between individual signers and a small effect for level of education, but not for other sociolinguistic variables. Our results provide genuine evidence that mouthings form an inextricable component of signed interaction. Rather than displaying effects of competition between languages or spoken language suppression, NGT signers demonstrate the potential of the visual modality to conjoin parallel information streams.

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.

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