Phonological parameters in Croatian Sign Language

2006 ◽  
Vol 9 (1-2) ◽  
pp. 33-70 ◽  
Author(s):  
Ninoslava Šarac Kuhn ◽  
Tamara Alibašić Ciciliani ◽  
Ronnie B. Wilbur
Keyword(s):  
Sign Language ◽  
Prosodic Features ◽  
Sign Languages ◽  
Phonological Structure ◽  
Minimal Pairs ◽  
Sign Structure ◽  
Initial Description ◽  
Movement Orientation ◽  
Do So

We present an initial description of the sign parameters in Croatian Sign Language. We show that HZJ has a comparable phonological structure to other known sign languages, including basic sign parts, such as location, handshape, movement, orientation, and nonmanual characteristics. Our discussion follows the Prosodic Model (Brentari 1998), in which sign structure is separated into those characteristics which do not change during sign formation (inherent features) and those that do (prosodic features). We present the model, along with discussion of the notion of constraints on sign formation, and apply it to HZJ to the extent that we are able to do so. We identify an inventory of the relevant handshapes, orientations, locations, and movements in HZJ, and a partial inventory of nonmanuals. One interesting feature of the HZJ environment is the existence of two fingerspelling alphabets, a one-handed and a two-handed system. We also provide additional analytical steps that can be taken after the initial inventory has been constructed. Both minimal pairs and constraints on sign formation are especially useful for demonstrating the linguistic systematicity of sign languages and separating them from gesture and mime.

Evidence for minimal pairs in Turkish Sign Language (TİD)

2014 ◽  
Vol 50 (3) ◽  
pp. 207-230
Author(s):  
Bahtiyar Makaroğlu ◽  
İpek Pınar Bekar ◽  
Engin Arik
Keyword(s):  
Sign Language ◽  
Feature Classification ◽  
Close Attention ◽  
Sign Languages ◽  
Place Of Articulation ◽  
Phonological Structure ◽  
Research Perspectives ◽  
Minimal Pairs ◽  
Phonological Features ◽  
British Sign

Abstract Recently, many studies have examined the phonological parameters in sign languages from various research perspectives, paying close attention in particular to manual parameters such as handshape, place of articulation, movement, and orientation of the hands. However, these studies have been conducted on only a few sign languages such as American and British Sign Languages, and have paid little attention to nonmanual features. In this study, we investigated yet another sign language, Turkish Sign Language (TİD), focusing on both manual and nonmanual features to examine "minimal pairs", a cornerstone concept of phonology. We applied Brentari's (2005) feature classification and Pfau and Quer's (2010) phonological (or lexical) nonmanual categorization. Our analysis showed that both phonological features and constraints on TİD sign formation have a phonological structure similar to other well-studied sign languages. The results indicate that not only are phonological features a necessary notion for the description of both manual and nonmanual parameters at the lexical level in TİD, but also that nonmanuals have to be considered an essential part of sign as a way of better understanding their phonological roles in sign language phonology.

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.

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.

scholarly journals Sign Language Linguistics

Linguistics ◽  
2014 ◽  
Author(s):  
Carl Börstell ◽  
Wendy Sandler ◽  
Mark Aronoff
Keyword(s):  
American Sign Language ◽  
Sign Language ◽  
Theoretical Models ◽  
Human Cognition ◽  
Social Environments ◽  
Grammatical Structure ◽  
Sign Languages ◽  
Phonological Structure ◽  
Linguistic Research ◽  
The 1960S

Sign language linguistics is one of the younger areas of linguistic research, having been a field in its own right only since the 1960s, when the first research investigating sign languages from a linguistic perspective was published. Since sign language was historically considered not to be language at all, but merely a gesture-based aid for basic communication, early research was focused on demonstrating the linguistic status of sign languages—that they are indeed languages in their own right, equivalent to spoken languages. The earliest research used traditional linguistic tools to investigate the phonological structure of sign language (specifically American Sign Language [ASL]), and to demonstrate that sign languages had duality of patterning, but the field soon expanded in all directions. Within the following decades, more in-depth analyses of the phonological and grammatical structure of sign languages were published, as well as investigations on the acquisition and use of sign language. With time, existing theoretical models for spoken language were applied to sign languages as well, and a number of new models for representing the syntax and phonology of sign languages were introduced. Cross-linguistic research on different sign languages, as well as on different social environments (e.g., urban versus village sign languages), has become more and more popular, as have cross-modal comparisons with spoken languages. In applied fields of linguistics, education and interpreting have become two of the main areas of investigation, as has the study of sign language in artistic use (e.g., poetry), often in close connection to the field of deaf studies. The interface between sign language and gesture has become a hot topic, especially within the domains of language emergence and foundations of human cognition. Finally, neurolinguistics has also expanded to include sign language within the scope of research.

scholarly journals Formal variation in the Kata Kolok lexicon

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Hannah Lutzenberger ◽  
Connie de Vos ◽  
Onno Crasborn ◽  
Paula Fikkert
Keyword(s):  
Sign Language ◽  
Comprehensive Approach ◽  
Sign Languages ◽  
Village Community ◽  
Token Frequency ◽  
Phonological Structure ◽  
Language Emergence ◽  
Different Levels ◽  
Combining Methods ◽  
Frequency Weightings

Sign language lexicons incorporate phonological specifications. Evidence from emerging sign languages suggests that phonological structure emerges gradually in a new language. In this study, we investigate variation in the form of signs across 20 deaf adult signers of Kata Kolok, a sign language that emerged spontaneously in a Balinese village community. Combining methods previously used for sign comparisons, we introduce a new numeric measure of variation. Our nuanced yet comprehensive approach to form variation integrates three levels (iconic motivation, surface realisation, feature differences) and allows for refinement through weighting the variation score by token and signer frequency. We demonstrate that variation in the form of signs appears in different degrees at different levels. Token frequency in a given dataset greatly affects how much variation can surface, suggesting caution in interpreting previous findings. Different sign variants have different scopes of use among the signing population, with some more widely used than others. Both frequency weightings (token and signer) identify dominant sign variants, i.e., sign forms that are produced frequently or by many signers. We argue that variation does not equal the absence of conventionalisation. Indeed, especially in micro-community sign languages, variation may be key to understanding patterns of language emergence.

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 The sound of gender – correlations of name phonology and gender across languages

Linguistics ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tanja Ackermann ◽  
Christian Zimmer
Keyword(s):  
Sound Symbolism ◽  
Related Individual ◽  
Phonological Structure ◽  
Same Gender ◽  
And Gender ◽  
Germanic Languages ◽  
Do So

Abstract Our article is dedicated to the relation of a given name’s phonological structure and the gender of the referent. Phonology has been shown to play an important role with regard to gender marking on a name in some (Germanic) languages. For example, studies on English and on German have shown in detail that female and male names have significantly different phonological structures. However, little is known whether these phonological patterns are valid beyond (closely related) individual languages. This study, therefore, sets out to assess the relation of gender and the phonological structures of names across different languages/cultures. In order to do so, we analyzed a sample of popular given names from 13 countries. Our results indicate that there are both language/culture-overarching similarities between names used for people of the same gender and language/culture-specific correlations. Finally, our results are interpreted against the backdrop of conventional and synesthetic sound symbolism.

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.

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