scholarly journals Using depiction for efficient communication in LIS (Italian Sign Language)

2021 ◽  
pp. 1-30
Author(s):  
ANITA SLONIMSKA ◽  
ASLI ÖZYÜREK ◽  
OLGA CAPIRCI

abstract Meanings communicated with depictions constitute an integral part of how speakers and signers actually use language (Clark, 2016). Recent studies have argued that, in sign languages, depicting strategy like constructed action (CA), in which a signer enacts the referent, is used for referential purposes in narratives. Here, we tested the referential function of CA in a more controlled experimental setting and outside narrative context. Given the iconic properties of CA we hypothesized that this strategy could be used for efficient information transmission. Thus, we asked if use of CA increased with the increase in the information required to be communicated. Twenty-three deaf signers of LIS described unconnected images, which varied in the amount of information represented, to another player in a director–matcher game. Results revealed that participants used CA to communicate core information about the images and also increased the use of CA as images became informatively denser. The findings show that iconic features of CA can be used for referential function in addition to its depictive function outside narrative context and to achieve communicative efficiency.

1991 ◽  
Vol 20 (1) ◽  
pp. 37-57 ◽  
Author(s):  
Jill Jepson

ABSTRACTA comparison is presented of Indian urban and rural sign languages of the deaf. The structures of both languages are designed for efficient communication but have developed differently in response to different sociolinguistic environments. The urban form transmits information primarily by means of appeal to a shared linguistic code; the rural form mainly by appeal to communal nonlinguistic knowledge. Both languages employ effective and appropriate means given their environments. The relationship between language usage and structure is explored. (Sign language, deafness, India)


2020 ◽  
Vol 37 (4) ◽  
pp. 571-608
Author(s):  
Diane Brentari ◽  
Laura Horton ◽  
Susan Goldin-Meadow

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.


2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Gustaf Halvardsson ◽  
Johanna Peterson ◽  
César Soto-Valero ◽  
Benoit Baudry

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.


Author(s):  
Marion Kaczmarek ◽  
Michael Filhol

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.


2021 ◽  
Vol 14 (2) ◽  
pp. 1-45
Author(s):  
Danielle Bragg ◽  
Naomi Caselli ◽  
Julie A. Hochgesang ◽  
Matt Huenerfauth ◽  
Leah Katz-Hernandez ◽  
...  

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.


2021 ◽  
pp. 095679762199155
Author(s):  
Amanda R. Brown ◽  
Wim Pouw ◽  
Diane Brentari ◽  
Susan Goldin-Meadow

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.


2019 ◽  
Vol 5 (1) ◽  
pp. 666-689
Author(s):  
Carl Börstell ◽  
Tommi Jantunen ◽  
Vadim Kimmelman ◽  
Vanja de Lint ◽  
Johanna Mesch ◽  
...  

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.


1999 ◽  
Vol 2 (2) ◽  
pp. 187-215 ◽  
Author(s):  
Wendy Sandler

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.


2016 ◽  
Vol 28 (1) ◽  
pp. 20-40 ◽  
Author(s):  
Velia Cardin ◽  
Eleni Orfanidou ◽  
Lena Kästner ◽  
Jerker Rönnberg ◽  
Bencie Woll ◽  
...  

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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