Search results for: Indian sign language
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5021

Search results for: Indian sign language

5021 Mouthing Patterns in Indian Sign Language

Authors: Neha Kulshreshtha

Abstract:

This paper examines the patterns of 'Mouthing', a non-manual marker, and its distribution in Indian Sign Language (ISL). Linguistic research in Indian Sign Language is an emerging field where much is needed to be done. The little research which has happened focuses on the structure of ISL in terms of physical or manual markers, therefore a study of mouthing patterns would give an insight into the distribution of this particular non-manual marker. Data has been collected with the help of native ISL users through various techniques in which natural signs can be captured, for example, storytelling, informal conversations etc. The aim of the study is to find out the various situations where mouthing is used. Sometimes, the mouthing is not actually the articulation of the word as spoken in the local languages. The paper aims to find out whether the mouthing patterns in ISL are influenced by any local language or they are independent of any influence from the local language or both. Mouthing patterns have been studied in many sign languages and an investigation into ISL will reveal whether it falls in pattern with the other sign languages.

Keywords: Indian sign language, mouthing, non-manual marker, spoken language influence

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5020 Online Multilingual Dictionary Using Hamburg Notation for Avatar-Based Indian Sign Language Generation System

Authors: Sugandhi, Parteek Kumar, Sanmeet Kaur

Abstract:

Sign Language (SL) is used by deaf and other people who cannot speak but can hear or have a problem with spoken languages due to some disability. It is a visual gesture language that makes use of either one hand or both hands, arms, face, body to convey meanings and thoughts. SL automation system is an effective way which provides an interface to communicate with normal people using a computer. In this paper, an avatar based dictionary has been proposed for text to Indian Sign Language (ISL) generation system. This research work will also depict a literature review on SL corpus available for various SL s over the years. For ISL generation system, a written form of SL is required and there are certain techniques available for writing the SL. The system uses Hamburg sign language Notation System (HamNoSys) and Signing Gesture Mark-up Language (SiGML) for ISL generation. It is developed in PHP using Web Graphics Library (WebGL) technology for 3D avatar animation. A multilingual ISL dictionary is developed using HamNoSys for both English and Hindi Language. This dictionary will be used as a database to associate signs with words or phrases of a spoken language. It provides an interface for admin panel to manage the dictionary, i.e., modification, addition, or deletion of a word. Through this interface, HamNoSys can be developed and stored in a database and these notations can be converted into its corresponding SiGML file manually. The system takes natural language input sentence in English and Hindi language and generate 3D sign animation using an avatar. SL generation systems have potential applications in many domains such as healthcare sector, media, educational institutes, commercial sectors, transportation services etc. This research work will help the researchers to understand various techniques used for writing SL and generation of Sign Language systems.

Keywords: avatar, dictionary, HamNoSys, hearing impaired, Indian sign language (ISL), sign language

Procedia PDF Downloads 187
5019 Hand Motion Trajectory Analysis for Dynamic Hand Gestures Used in Indian Sign Language

Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

Abstract:

Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

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5018 Real-Time Gesture Recognition System Using Microsoft Kinect

Authors: Ankita Wadhawan, Parteek Kumar, Umesh Kumar

Abstract:

Gesture is any body movement that expresses some attitude or any sentiment. Gestures as a sign language are used by deaf people for conveying messages which helps in eliminating the communication barrier between deaf people and normal persons. Nowadays, everybody is using mobile phone and computer as a very important gadget in their life. But there are some physically challenged people who are blind/deaf and the use of mobile phone or computer like device is very difficult for them. So, there is an immense need of a system which works on body gesture or sign language as input. In this research, Microsoft Kinect Sensor, SDK V2 and Hidden Markov Toolkit (HTK) are used to recognize the object, motion of object and human body joints through Touch less NUI (Natural User Interface) in real-time. The depth data collected from Microsoft Kinect has been used to recognize gestures of Indian Sign Language (ISL). The recorded clips are analyzed using depth, IR and skeletal data at different angles and positions. The proposed system has an average accuracy of 85%. The developed Touch less NUI provides an interface to recognize gestures and controls the cursor and click operation in computer just by waving hand gesture. This research will help deaf people to make use of mobile phones, computers and socialize among other persons in the society.

Keywords: gesture recognition, Indian sign language, Microsoft Kinect, natural user interface, sign language

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5017 Revitalization of Sign Language through Deaf Theatre: A Linguistic Analysis of an Art Form Which Combines Physical Theatre, Poetry, and Sign Language

Authors: Gal Belsitzman, Rose Stamp, Atay Citron, Wendy Sandler

Abstract:

Sign languages are considered endangered. The vitality of sign languages is compromised by its unique sociolinguistic situation, in which hearing parents that give birth to deaf children usually decide to cochlear implant their child. Therefore, these children don’t acquire their natural language – Sign Language. Despite this, many sign languages, such as Israeli Sign Language (ISL) are thriving. The continued survival of similar languages under threat has been associated with the remarkable resilience of the language community. In particular, deaf literary traditions are central in reminding the community of the importance of the language. One example of a deaf literary tradition which has received increased popularity in recent years is deaf theatre. The Ebisu Sign Language Theatre Laboratory, developed as part of the multidisciplinary Grammar of the Body Research Project, is the first deaf theatre company in Israel. Ebisu Theatre combines physical theatre and sign language research, to allow for a natural laboratory to analyze the creative use of the body. In this presentation, we focus on the recent theatre production called ‘Their language’ which tells of the struggle faced by the deaf community to use their own natural language in the education system. A thorough analysis unravels how linguistic properties are integrated with the use of poetic devices and physical theatre techniques in this performance, enabling wider access by both deaf and hearing audiences, without interpretation. Interviews with the audience illustrate the significance of this art form which serves a dual purpose, both as empowering for the deaf community and educational for the hearing and deaf audiences, by raising awareness of community-related issues.

Keywords: deaf theatre, empowerment, language revitalization, sign language

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5016 Brazilian Sign Language: A Synthesis of the Research in the Period from 2000 to 2017

Authors: Maria da Gloria Guara-Tavares

Abstract:

This article reports a synthesis of the research in Brazilian Sign Language conducted from 2000 to 2017. The objective of the synthesis was to identify the most researched areas and the most used methodologies. Articles published in three Brazilian journals of Translation Studies, unpublished dissertations and theses were included in the analysis. Abstracts and the method sections of the papers were scrutinized. Sixty studies were analyzed, and overall results indicate that the research in Brazilian Sign Language has been fragmented in several areas such as linguistic aspects, facial expressions, subtitling, identity issues, bilingualism, and interpretation strategies. Concerning research methods, the synthesis reveals that most research is qualitative in nature. Moreover, results show that the cognitive aspects of Brazilian Sign Language seem to be poorly explored. Implications for a future research agenda are also discussed.

Keywords: Brazilian sign language, qualitative methods, research agenda, synthesis

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5015 A Motion Dictionary to Real-Time Recognition of Sign Language Alphabet Using Dynamic Time Warping and Artificial Neural Network

Authors: Marcio Leal, Marta Villamil

Abstract:

Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: artificial neural network, computer vision, dynamic time warping, infrared, sign language recognition

Procedia PDF Downloads 176
5014 Comparison of Sign Language Skill and Academic Achievement of Deaf Students in Special and Inclusive Primary Schools of South Nation Nationalities People Region, Ethiopia

Authors: Tesfaye Basha

Abstract:

The purpose of this study was to examine the sign language and academic achievement of deaf students in special and inclusive primary schools of Southern Ethiopia. The study used a mixed-method to collect varied data. The study contained Signed Amharic and English skill tasks, questionnaire, 8th-grade Primary School Leaving Certificate Examination results, classroom observation, and interviews. For quantitative (n=70) deaf students and for qualitative data collection, 16 participants were involved. The finding revealed that the limitation of sign language is a problem in signing and academic achievements. This displays that schools are not linguistically rich to enable sign language achievement for deaf students. Moreover, the finding revealed that the contribution of Total Communication in the growth of natural sign language for deaf students was unsatisfactory. The results also indicated that special schools of deaf students performed better sign language skills and academic achievement than inclusive schools. In addition, the findings revealed that high signed skill group showed higher academic achievement than the low skill group. This displayed that sign language skill is highly associated with academic achievement. In addition, to qualify deaf students in sign language and academics, teacher institutions must produce competent teachers on how to teach deaf students with sign language and literacy skills.

Keywords: academic achievement, inclusive school, sign language, signed Amharic, signed English, special school, total communication

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5013 Prototyping a Portable, Affordable Sign Language Glove

Authors: Vidhi Jain

Abstract:

Communication between speakers and non-speakers of American Sign Language (ASL) can be problematic, inconvenient, and expensive. This project attempts to bridge the communication gap by designing a portable glove that captures the user’s ASL gestures and outputs the translated text on a smartphone. The glove is equipped with flex sensors, contact sensors, and a gyroscope to measure the flexion of the fingers, the contact between fingers, and the rotation of the hand. The glove’s Arduino UNO microcontroller analyzes the sensor readings to identify the gesture from a library of learned gestures. The Bluetooth module transmits the gesture to a smartphone. Using this device, one day speakers of ASL may be able to communicate with others in an affordable and convenient way.

Keywords: sign language, morse code, convolutional neural network, American sign language, gesture recognition

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5012 Transmigration of American Sign Language from the American Deaf Community to the American Society

Authors: Russell Rosen

Abstract:

American Sign Language (ASL) has been developed and used by signing deaf and hard of hearing (DHH) individuals in the American Deaf community since early nineteenth century. In the last two decades, secondary schools in the US offered ASL for foreign language credit to secondary school learners. The learners who learn ASL as a foreign language are largely American native speakers of English. They not only learn ASL in US schools but also create spaces under certain interactional and social conditions in their home communities outside of classrooms and use ASL with each other instead of their native English. This phenomenon is a transmigration of language from a native social group to a non-native, non-kin social group. This study looks at the transmigration of ASL from signing Deaf community to the general speaking and hearing American society. Theoretical implications of this study are discussed.

Keywords: American Sign Language, Foreign Language, Language transmission, United States

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5011 Development of Taiwanese Sign Language Receptive Skills Test for Deaf Children

Authors: Hsiu Tan Liu, Chun Jung Liu

Abstract:

It has multiple purposes to develop a sign language receptive skills test. For example, this test can be used to be an important tool for education and to understand the sign language ability of deaf children. There is no available test for these purposes in Taiwan. Through the discussion of experts and the references of standardized Taiwanese Sign Language Receptive Test for adults and adolescents, the frame of Taiwanese Sign Language Receptive Skills Test (TSL-RST) for deaf children was developed, and the items were further designed. After multiple times of pre-trials, discussions and corrections, TSL-RST is finally developed which can be conducted and scored online. There were 33 deaf children who agreed to be tested from all three deaf schools in Taiwan. Through item analysis, the items were picked out that have good discrimination index and fair difficulty index. Moreover, psychometric indexes of reliability and validity were established. Then, derived the regression formula was derived which can predict the sign language receptive skills of deaf children. The main results of this study are as follows. (1). TSL-RST includes three sub-test of vocabulary comprehension, syntax comprehension and paragraph comprehension. There are 21, 20, and 9 items in vocabulary comprehension, syntax comprehension, and paragraph comprehension, respectively. (2). TSL-RST can be conducted individually online. The sign language ability of deaf students can be calculated fast and objectively, so that they can get the feedback and results immediately. This can also contribute to both teaching and research. The most subjects can complete the test within 25 minutes. While the test procedure, they can answer the test questions without relying on their reading ability or memory capacity. (3). The sub-test of the vocabulary comprehension is the easiest one, syntax comprehension is harder than vocabulary comprehension and the paragraph comprehension is the hardest. Each of the three sub-test and the whole test are good in item discrimination index. (4). The psychometric indices are good, including the internal consistency reliability (Cronbach’s α coefficient), test-retest reliability, split-half reliability, and content validity. The sign language ability are significantly related to non-verbal IQ, the teachers’ rating to the students’ sign language ability and students’ self-rating to their own sign language ability. The results showed that the higher grade students have better performance than the lower grade students, and students with deaf parent perform better than those with hearing parent. These results made TLS-RST have great discriminant validity. (5). The predictors of sign language ability of primary deaf students are age and years of starting to learn sign language. The results of this study suggested that TSL-RST can effectively assess deaf student’s sign language ability. This study also proposed a model to develop a sign language tests.

Keywords: comprehension test, elementary school, sign language, Taiwan sign language

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5010 Assessing Language Dominance in Mexican Deaf Signers with the Bilingual Language Profile (BLP)

Authors: E. Mendoza, D. Jackson-Maldonado, G. Avecilla-Ramírez, A. Mondaca

Abstract:

Assessing language proficiency is a major issue in psycholinguistic research. There are multiple tools that measure language dominance and language proficiency in hearing bilinguals, however, this is not the case for Deaf bilinguals. Specifically, there are few, if not none, assessment tools useful in the description of the multilingual abilities of Mexican Deaf signers. Because of this, the linguistic characteristics of Mexican Deaf population have been poorly described. This paper attempts to explain the necessary changes done in order to adapt the Bilingual Language Profile (BLP) to Mexican Sign Language (LSM) and written/oral Spanish. BLP is a Self-Evaluation tool that has been adapted and translated to several oral languages, but not to sign languages. Lexical, syntactic, cultural, and structural changes were applied to the BLP. 35 Mexican Deaf signers participated in a pilot study. All of them were enrolled in Higher Education programs. BLP was presented online in written Spanish via Google Forms. No additional information in LSM was provided. Results show great heterogeneity as it is expected of Deaf populations and BLP seems to be a useful tool to create a bilingual profile of the Mexican Deaf population. This is a first attempt to adapt a widely tested tool in bilingualism research to sign language. Further modifications need to be done.

Keywords: deaf bilinguals, assessment tools, bilingual language profile, mexican sign language

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5009 Inclusive Cultural Heritage Tourism Project

Authors: L. Cruz-Lopes, M. Sell, P. Escudeiro, B. Esteves

Abstract:

It might be difficult for deaf people to communicate since spoken and written languages are different from sign language. When it comes to getting information, going to places of cultural heritage, or using services and infrastructure, there is a clear lack of inclusiveness. By creating assistive technology that enables deaf individuals to get around communication hurdles and encourage inclusive tourism, the ICHT- Inclusive Cultural Heritage Tourism initiative hopes to increase knowledge of sign language. The purpose of the Inclusive Cultural Heritage Tourism (ICHT) project is to develop online and on-site sign language tools and material for usage at popular tourist destinations in the northern region of Portugal, including Torre dos Clérigos, the Lello bookstore, Maia Zoo, Porto wine cellars, and São Pedro do Sul (Viseu) thermae. The ICHT system consists of an application using holography, a mobile game, an online platform for collaboration with deaf and hearing users, and a collection of International Sign training courses. The project also offers a prospect for a more inclusive society by introducing a method of teaching sign languages to tourism industry professionals. As a result, the teaching and learning of sign language along with the assistive technology tools created by the project sets up an inclusive environment for the deaf community, producing results in the area of automatic sign language translation and aiding in the global recognition of the Portuguese tourism industry.

Keywords: inclusive tourism, games, international sign training, deaf community

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5008 Facial Expression Phoenix (FePh): An Annotated Sequenced Dataset for Facial and Emotion-Specified Expressions in Sign Language

Authors: Marie Alaghband, Niloofar Yousefi, Ivan Garibay

Abstract:

Facial expressions are important parts of both gesture and sign language recognition systems. Despite the recent advances in both fields, annotated facial expression datasets in the context of sign language are still scarce resources. In this manuscript, we introduce an annotated sequenced facial expression dataset in the context of sign language, comprising over 3000 facial images extracted from the daily news and weather forecast of the public tv-station PHOENIX. Unlike the majority of currently existing facial expression datasets, FePh provides sequenced semi-blurry facial images with different head poses, orientations, and movements. In addition, in the majority of images, identities are mouthing the words, which makes the data more challenging. To annotate this dataset we consider primary, secondary, and tertiary dyads of seven basic emotions of "sad", "surprise", "fear", "angry", "neutral", "disgust", and "happy". We also considered the "None" class if the image’s facial expression could not be described by any of the aforementioned emotions. Although we provide FePh as a facial expression dataset of signers in sign language, it has a wider application in gesture recognition and Human Computer Interaction (HCI) systems.

Keywords: annotated facial expression dataset, gesture recognition, sequenced facial expression dataset, sign language recognition

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5007 Computerized Analysis of Phonological Structure of 10,400 Brazilian Sign Language Signs

Authors: Wanessa G. Oliveira, Fernando C. Capovilla

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Capovilla and Raphael’s Libras Dictionary documents a corpus of 4,200 Brazilian Sign Language (Libras) signs. Duduchi and Capovilla’s software SignTracking permits users to retrieve signs even when ignoring the gloss corresponding to it and to discover the meaning of all 4,200 signs sign simply by clicking on graphic menus of the sign characteristics (phonemes). Duduchi and Capovilla have discovered that the ease with which any given sign can be retrieved is an inverse function of the average popularity of its component phonemes. Thus, signs composed of rare (distinct) phonemes are easier to retrieve than are those composed of common phonemes. SignTracking offers a means of computing the average popularity of the phonemes that make up each one of 4,200 signs. It provides a precise measure of the degree of ease with which signs can be retrieved, and sign meanings can be discovered. Duduchi and Capovilla’s logarithmic model proved valid: The degree with which any given sign can be retrieved is an inverse function of the arithmetic mean of the logarithm of the popularity of each component phoneme. Capovilla, Raphael and Mauricio’s New Libras Dictionary documents a corpus of 10,400 Libras signs. The present analysis revealed Libras DNA structure by mapping the incidence of 501 sign phonemes resulting from the layered distribution of five parameters: 163 handshape phonemes (CherEmes-ManusIculi); 34 finger shape phonemes (DactilEmes-DigitumIculi); 55 hand placement phonemes (ArtrotoToposEmes-ArticulatiLocusIculi); 173 movement dimension phonemes (CinesEmes-MotusIculi) pertaining to direction, frequency, and type; and 76 Facial Expression phonemes (MascarEmes-PersonalIculi).

Keywords: Brazilian sign language, lexical retrieval, libras sign, sign phonology

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5006 Irreducible Sign Patterns of Minimum Rank of 3 and Symmetric Sign Patterns That Allow Diagonalizability

Authors: Sriparna Bandopadhyay

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It is known that irreducible sign patterns in general may not allow diagonalizability and in particular irreducible sign patterns with minimum rank greater than or equal to 4. It is also known that every irreducible sign pattern matrix with minimum rank of 2 allow diagonalizability with rank of 2 and the maximum rank of the sign pattern. In general sign patterns with minimum rank of 3 may not allow diagonalizability if the condition of irreducibility is dropped, but the problem of whether every irreducible sign pattern with minimum rank of 3 allows diagonalizability remains open. In this paper it is shown that irreducible sign patterns with minimum rank of 3 under certain conditions on the underlying graph allow diagonalizability. An alternate proof of the results that every sign pattern matrix with minimum rank of 2 and no zero lines allow diagonalizability with rank of 2 and also that every full sign pattern allows diagonalizability with all permissible ranks of the sign pattern is given. Some open problems regarding composite cycles in an irreducible symmetric sign pattern that support of a rank principal certificate are also answered.

Keywords: irreducible sign patterns, minimum rank, symmetric sign patterns, rank -principal certificate, allowing diagonalizability

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5005 Sign Language Recognition of Static Gestures Using Kinect™ and Convolutional Neural Networks

Authors: Rohit Semwal, Shivam Arora, Saurav, Sangita Roy

Abstract:

This work proposes a supervised framework with deep convolutional neural networks (CNNs) for vision-based sign language recognition of static gestures. Our approach addresses the acquisition and segmentation of correct inputs for the CNN-based classifier. Microsoft Kinect™ sensor, despite complex environmental conditions, can track hands efficiently. Skin Colour based segmentation is applied on cropped images of hands in different poses, used to depict different sign language gestures. The segmented hand images are used as an input for our classifier. The CNN classifier proposed in the paper is able to classify the input images with a high degree of accuracy. The system was trained and tested on 39 static sign language gestures, including 26 letters of the alphabet and 13 commonly used words. This paper includes a problem definition for building the proposed system, which acts as a sign language translator between deaf/mute and the rest of the society. It is then followed by a focus on reviewing existing knowledge in the area and work done by other researchers. It also describes the working principles behind different components of CNNs in brief. The architecture and system design specifications of the proposed system are discussed in the subsequent sections of the paper to give the reader a clear picture of the system in terms of the capability required. The design then gives the top-level details of how the proposed system meets the requirements.

Keywords: sign language, CNN, HCI, segmentation

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5004 Lithuanian Sign Language Literature: Metaphors at the Phonological Level

Authors: Anželika Teresė

Abstract:

In order to solve issues in sign language linguistics, address matters pertaining to maintaining high quality of sign language (SL) translation, contribute to dispelling misconceptions about SL and deaf people, and raise awareness and understanding of the deaf community heritage, this presentation discusses literature in Lithuanian Sign Language (LSL) and inherent metaphors that are created by using the phonological parameter –handshape, location, movement, palm orientation and nonmanual features. The study covered in this presentation is twofold, involving both the micro-level analysis of metaphors in terms of phonological parameters as a sub-lexical feature and the macro-level analysis of the poetic context. Cognitive theories underlie research of metaphors in sign language literature in a range of SL. The study follows this practice. The presentation covers the qualitative analysis of 34 pieces of LSL literature. The analysis employs ELAN software widely used in SL research. The target is to examine how specific types of each phonological parameter are used for the creation of metaphors in LSL literature and what metaphors are created. The results of the study show that LSL literature employs a range of metaphors created by using classifier signs and by modifying the established signs. The study also reveals that LSL literature tends to create reference metaphors indicating status and power. As the study shows, LSL poets metaphorically encode status by encoding another meaning in the same sign, which results in creating double metaphors. The metaphor of identity has been determined. Notably, the poetic context has revealed that the latter metaphor can also be identified as a metaphor for life. The study goes on to note that deaf poets create metaphors related to the importance of various phenomena significance of the lyrical subject. Notably, the study has allowed detecting locations, nonmanual features and etc., never mentioned in previous SL research as used for the creation of metaphors.

Keywords: Lithuanian sign language, sign language literature, sign language metaphor, metaphor at the phonological level, cognitive linguistics

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5003 Pattern Recognition Based on Simulation of Chemical Senses (SCS)

Authors: Nermeen El Kashef, Yasser Fouad, Khaled Mahar

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No AI-complete system can model the human brain or behavior, without looking at the totality of the whole situation and incorporating a combination of senses. This paper proposes a Pattern Recognition model based on Simulation of Chemical Senses (SCS) for separation and classification of sign language. The model based on human taste controlling strategy. The main idea of the introduced model is motivated by the facts that the tongue cluster input substance into its basic tastes first, and then the brain recognizes its flavor. To implement this strategy, two level architecture is proposed (this is inspired from taste system). The separation-level of the architecture focuses on hand posture cluster, while the classification-level of the architecture to recognizes the sign language. The efficiency of proposed model is demonstrated experimentally by recognizing American Sign Language (ASL) data set. The recognition accuracy obtained for numbers of ASL is 92.9 percent.

Keywords: artificial intelligence, biocybernetics, gustatory system, sign language recognition, taste sense

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5002 A Novel Combined Finger Counting and Finite State Machine Technique for ASL Translation Using Kinect

Authors: Rania Ahmed Kadry Abdel Gawad Birry, Mohamed El-Habrouk

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This paper presents a brief survey of the techniques used for sign language recognition along with the types of sensors used to perform the task. It presents a modified method for identification of an isolated sign language gesture using Microsoft Kinect with the OpenNI framework. It presents the way of extracting robust features from the depth image provided by Microsoft Kinect and the OpenNI interface and to use them in creating a robust and accurate gesture recognition system, for the purpose of ASL translation. The Prime Sense’s Natural Interaction Technology for End-user - NITE™ - was also used in the C++ implementation of the system. The algorithm presents a simple finger counting algorithm for static signs as well as directional Finite State Machine (FSM) description of the hand motion in order to help in translating a sign language gesture. This includes both letters and numbers performed by a user, which in-turn may be used as an input for voice pronunciation systems.

Keywords: American sign language, finger counting, hand tracking, Microsoft Kinect

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5001 TechWhiz: Empowering Deaf Students through Inclusive Education

Authors: Paula Escudeiro, Nuno Escudeiro, Márcia Campos, Francisca Escudeiro

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In today's world, technical and scientific knowledge plays a vital role in education, research, and employment. Deaf students face unique challenges in educational settings, particularly when it comes to understanding technical and scientific terminology. The reliance on written and spoken languages can create barriers for deaf individuals who primarily communicate using sign language. This lack of accessibility can hinder their learning experience and compromise equity in education. To address this issue, the TechWhiz project has been developed as a comprehensive glossary of scientific and technical concepts explained in sign language. By providing deaf students with access to education in their first language, TechWhiz aims to enhance their learning achievements and promote inclusivity while also fostering equity in education for all students.

Keywords: deaf students, technical and scientific knowledge, automatic sign language, inclusive education

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5000 Need for E-Learning: An Effective Method in Educating the Persons with Hearing Impairment Using Sign Language

Authors: S. Vijayakumar, S. B. Rathna Kumar, Navnath D Jagadale

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Learning and teaching are the challenges ahead in the education of the students with hearing impairment using sign language (SHISL). Either the students or teachers face difficulties in the process of learning/teaching. Communication is one of the main barriers while teaching SHISL. Further, the courses of study or the subjects are limited to SHISL at least in countries like India. Students with hearing impairment mainly opt for sign language as a communication mode. Subjects like physics, chemistry, advanced mathematics etc. are not available in the curriculum for the SHISL since their content and ideas are complex. In India, exemption for language papers is being given for the students with hearing impairment. It may give opportunity to them to secure secondary/ higher secondary qualifications. It is a known fact that students with hearing impairment are facing difficulty in their future carrier. They secure neither a higher study nor a good employment opportunity. Vocational training in various trades will land them in few jobs with few bucks in pocket. However, not all of them are blessed with higher positions in government or private sectors in competitive fields or where the technical knowledge is required. E learning with sign language instructions can be used for teaching languages and science subjects. Computer Based Instruction (CBI), Computer Based Training (CBT), and Computer Assisted Instruction (CAI) are now part-and-parcel of Modern Education. It will also include signed video clip corresponding to the topic. Learning language subjects will improve the understanding of concepts in different subjects. Learning other science subjects like their hearing counterparts will enable the SHISL to go higher in studies and increase their height to pluck a fruit of the tree of employment.

Keywords: students with hearing impairment using sign language, hearing impairment, language subjects, science subjects, e-learning

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4999 Bahasa Melayu Hand Coded and Malaysian Sign Language Acquisition of Hearing Impaired Students at Early Intervention

Authors: Abdul Rahim Razalli, Nordin Mamat, Lee Kean Low

Abstract:

The objective of the study is to examine the acquisition of Bahasa Melayu hand coded and Malaysian Sign Language of hearing impaired children and the factors that influencing the acquisition of Malay language at early intervention. A qualitative research design was chosen to answer two research questions. Two sets of instruments have been used to obtain information of proficiency and factors that influence it. Five children with hearing problems, four teachers and three parents were selected as the respondents through purposive sampling technique. The findings show that pupils with hearing problems who mastered Bahasa Melayu hand coded have better acquisition of Bahasa Melayu as compared to those who acquired Malaysian Sign Language. The study also found that the parents, pupils, teachers and environmental factors have an impact on the acquisition of Bahasa Melayu hand coded. The implications of this study show that early intervention of Bahasa Melayu hand coded and the parents, pupils, teachers and environmental factors do help in the language proficiency of children with hearing problems. A more comprehensive study should be undertaken at a higher level to see the impact on an early intervention program for Malay language acquisition of hearing impaired children.

Keywords: Bahasa Melayu hand coded, Malaysian sign Language, hearing impaired children, early intervention

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4998 Hand Detection and Recognition for Malay Sign Language

Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Norhafilah Bara

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Developing a software application using an interface with computers and peripheral devices using gestures of human body such as hand movements keeps growing in interest. A review on this hand gesture detection and recognition based on computer vision technique remains a very challenging task. This is to provide more natural, innovative and sophisticated way of non-verbal communication, such as sign language, in human computer interaction. Nevertheless, this paper explores hand detection and hand gesture recognition applying a vision based approach. The hand detection and recognition used skin color spaces such as HSV and YCrCb are applied. However, there are limitations that are needed to be considered. Almost all of skin color space models are sensitive to quickly changing or mixed lighting circumstances. There are certain restrictions in order for the hand recognition to give better results such as the distance of user’s hand to the webcam and the posture and size of the hand.

Keywords: hand detection, hand gesture, hand recognition, sign language

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4997 Methodological Proposal, Archival Thesaurus in Colombian Sign Language

Authors: Pedro A. Medina-Rios, Marly Yolie Quintana-Daza

Abstract:

Having the opportunity to communicate in a social, academic and work context is very relevant for any individual and more for a deaf person when oral language is not their natural language, and written language is their second language. Currently, in Colombia, there is not a specialized dictionary for our best knowledge in sign language archiving. Archival is one of the areas that the deaf community has a greater chance of performing. Nourishing new signs in dictionaries for deaf people extends the possibility that they have the appropriate signs to communicate and improve their performance. The aim of this work was to illustrate the importance of designing pedagogical and technological strategies of knowledge management, for the academic inclusion of deaf people through proposals of lexicon in Colombian sign language (LSC) in the area of archival. As a method, the analytical study was used to identify relevant words in the technical area of the archival and its counterpart with the LSC, 30 deaf people, apprentices - students of the Servicio Nacional de Aprendizaje (SENA) in Documentary or Archival Management programs, were evaluated through direct interviews in LSC. For the analysis tools were maintained to evaluate correlation patterns and linguistic methods of visual, gestural analysis and corpus; besides, methods of linear regression were used. Among the results, significant data were found among the variables socioeconomic stratum, academic level, labor location. The need to generate new signals on the subject of the file to improve communication between the deaf person, listener and the sign language interpreter. It is concluded that the generation of new signs to nourish the LSC dictionary in archival subjects is necessary to improve the labor inclusion of deaf people in Colombia.

Keywords: archival, inclusion, deaf, thesaurus

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4996 Signed Language Phonological Awareness: Building Deaf Children's Vocabulary in Signed and Written Language

Authors: Lynn Mcquarrie, Charlotte Enns

Abstract:

The goal of this project was to develop a visually-based, signed language phonological awareness training program and to pilot the intervention with signing deaf children (ages 6 -10 years/ grades 1 - 4) who were beginning readers to assess the effects of systematic explicit American Sign Language (ASL) phonological instruction on both ASL vocabulary and English print vocabulary learning. Growing evidence that signing learners utilize visually-based signed language phonological knowledge (homologous to the sound-based phonological level of spoken language processing) when reading underscore the critical need for further research on the innovation of reading instructional practices for visual language learners. Multiple single-case studies using a multiple probe design across content (i.e., sign and print targets incorporating specific ASL phonological parameters – handshapes) was implemented to examine if a functional relationship existed between instruction and acquisition of these skills. The results indicated that for all cases, representing a variety of language abilities, the visually-based phonological teaching approach was exceptionally powerful in helping children to build their sign and print vocabularies. Although intervention/teaching studies have been essential in testing hypotheses about spoken language phonological processes supporting non-deaf children’s reading development, there are no parallel intervention/teaching studies exploring hypotheses about signed language phonological processes in supporting deaf children’s reading development. This study begins to provide the needed evidence to pursue innovative teaching strategies that incorporate the strengths of visual learners.

Keywords: American sign language phonological awareness, dual language strategies, vocabulary learning, word reading

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4995 Teacher Education in a Bilingual Perspective: Brazilian Sign Language and Portuguese

Authors: Neuma Chaveiro, Juliana Guimarães Faria

Abstract:

Introduction: The thematic that guides this study is teacher training for the teaching of sign language in a perspective of bilingual education – specifically aimed at Brazilian public schools that offer inclusive education, and that have, among its students, deaf children who use Brazilian Sign Language as a means of communication and expression. In the Teacher Training Course for Letters/Libras at the Universidade Federal de Goiás/UFG, we developed a bilingual education project for the deaf, linked to PIBID (Institutional Scholarship for Teaching Initiation Program), funded by the Brazilian Federal Government through CAPES (Coordination for the Improvement of Higher Education Personnel). Goals: to provide the education of higher education teachers to work in public schools in basic education and to insert students from the UFG’s Letters/Libras course in the school’s daily life, giving them the opportunity for the creation and participation in methodological experiences and of teaching practices in order to overcome the problems identified in the teaching-learning process of deaf students, in a bilingual perspective, associating Libras (Brazilian Sign Language) and Portuguese. Methodology: qualitative approach and research-action, prioritizing action – reflection – action of the people involved. The Letters-Libras PIBID of the College of Letters/UFG, in this qualitative context, is guided by the assumptions of investigation-action to contribute to the education of the Libras teacher. Results: production of studies and researches in the area of education, professionalization and teaching practice for the degree holder in Letters: Libras; b) studies, research and training in bilingual education; c) clarification and discussion of the myths that permeate the reality of users of sign languages; d) involving students in the development of didactic materials for bilingual education. Conclusion: the PIBID Project Letters/Libras allows, both to the basic education school and to the teachers in training for the teaching of Libras, an integrated and collective work partnership, with discussions and changes in relation to bilingual education for the deaf and the teaching of Libras.

Keywords: deaf, sign language, teacher training, educacion

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4994 Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

Abstract:

Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

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4993 Solving Definition and Relation Problems in English Navigation Terminology

Authors: Ayşe Yurdakul, Eckehard Schnieder

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Because of the growing multidisciplinarity and multilinguality, communication problems in different technical fields grows more and more. Therefore, each technical field has its own specific language, terminology which is characterised by the different definition of terms. In addition to definition problems, there are also relation problems between terms. Among these problems of relation, there are the synonymy, antonymy, hypernymy/hyponymy, ambiguity, risk of confusion, and translation problems etc. Thus, the terminology management system iglos of the Institute for Traffic Safety and Automation Engineering of the Technische Universität Braunschweig has the target to solve these problems by a methodological standardisation of term definitions with the aid of the iglos sign model and iglos relation types. The focus of this paper should be on solving definition and relation problems between terms in English navigation terminology.

Keywords: iglos, iglos sign model, methodological resolutions, navigation terminology, common language, technical language, positioning, definition problems, relation problems

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4992 Vision-Based Hand Segmentation Techniques for Human-Computer Interaction

Authors: M. Jebali, M. Jemni

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This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

Procedia PDF Downloads 369