Interpretation Of Signs Research Articles

Deaf migrants in Sweden: exploring linguistic and bureaucratic challenges through the lens of Crip Theory and Crip Linguistics

Abstract Disabled people encounter numerous barriers to accessibility and face discrimination and inequalities in their daily lives. The situation is even more complex for migrants with a disability, who have to learn how to navigate a new bureaucratic system. This study focuses on deaf adult migrants and the linguistic and bureaucratic challenges they face in Swedish society. The data consists of interviews with 43 deaf migrants participating in language learning courses in four folk high schools catering to deaf people in Sweden. Crip Theory and Crip Linguistics are used as lenses to explore the impact of able-bodiedness and linguistic norms on this particular group. The findings show that deaf migrants experience infantilisation, that sign language interpreters are often seen as a one-size-fits-all solution without much consideration for other factors influencing communication, and that normative able-bodiedness underlies many of the bureaucratic issues deaf migrants face.

Perception of deaf patients about medical care

Deaf people are those who understand and interact with the world through visual language. Due to the linguistic and cultural differences that characterize the deaf population, this group still faces difficulties in accessing health services. For this reason, it was proposed to investigate communication difficulties in providing care to deaf patients. This is a qualitative study which was carried out at the Association of the Deaf of Maranhão (ASMA), in São Luís. The sample consisted of 10 women and 10 men, all over the age of 18. The information was collected through semi-structured interviews, with the help of Brazilian Sign Language (LIBRAS) interpreters. Data interpretation were performed based on thematic content analysis. Two thematic categories were identified: “communication” and “autonomy”. In the first, the interviewees pointed out the lack of knowledge of the doctors about the needs of the deaf community or about their language, LIBRAS. In an attempt to establish a dialogue, the patients reported the use of writing, gestures and orofacial reading during the consultations. These strategies, however, are insufficient, since the information cannot be well understood. The second evidenced the need for the presence of companions to mediate the dialogue, as the participants stated that they did not find LIBRAS interpreters in the health units, resulting in loss of autonomy and confidentiality of information. It is concluded that this scenario of adversity implies important consequences for the health of this population, as well as lower adherence to treatments and a decrease in the search for medical care.

We May Be Visually or Hearing Impaired, but We Need Access to Visual and Auditory Information

This study explored access to information by visually and hearing-impaired patrons at the selected public libraries in Drakenstein Municipality: Paarl, Drakenstein, and Groenheuwel. The three Drakenstein Municipality public libraries were selected because they collaborate with the South African Library for the Blind (SALB) mini-library project to provide information services for the visually and hearing-impaired patrons. Participants were selected through purposive and snowball sampling within targeted public libraries and Drakenstein communities, respectively. Qualitative data were collected through interviews with visually and hearing-impaired patrons, SALB project coordinators, sign language interpreters, library assistants, and librarians responsible for providing service to visually and hearing-impaired patrons. Document analysis and observation were also used to supplement the data collected through interviews. The data were analyzed using content and thematic analysis. The study revealed that none of the three libraries had a specific policy or set of guidelines in place to meet the information needs of visually- and hearing-impaired patrons. Furthermore, the study established that the visually impaired have limited access to braille resources and audiobook collections. It is recommended that the three libraries develop a policy addressing information access issues for visually and hearing-impaired patrons.

Design a smart platform translating Arabic sign language to English language

Sign language is the only means of communication for deaf and hearing-disabled people in their communities. It uses body language and gestures, such as hand shapes and facial expressions, to convey a message. It is important to note that sign language is specific to the region; that is, Arabic sign language (ArSL) is different from English sign language. Therefore, this research proposes a way to improve the translation of ArSL using a new artificial intelligence (AI) architecture. Specifically, a convolutional neural network (CNN) based on fine-tuning of the SSD-ResNet50 V1 FPN is applied to build a real-time ArSL recognition and translation system with fast and accurate results. The proposed AI architecture can provide translation of sign language in real-time to enhance communication in the deaf community. We achieved an average F-score of 86% and an average accuracy of 94%.

Translation of Outdoor Signs in Nusa Dua Beach Area

This research was conducted to have a closer look at Linguistic Landscape in one of coastal areas of Bali, Indonesia. It specifically conducted with the aim of analyzing the translation of outdoor signs, in the form of notice or information boards. This research also examines translation shifts occur within those outdoor signs. This research is a qualitative descriptive study. The method applied for this research is observation method and include image capture and also note-taking technique. The problem formulated in this research applies Linguistic Landscape theory by Landry and Bourhis and also Translation Shift theory by Catford and Simatupang. The result of the research found that the form of translation of the outdoor signs in Nusa Dua beach area can be seen in the form of Notice board, cemented sign, or colored banner which has function to give information or warning to the people who visit the area. It also can be found that the shift occurs in the translation of the outdoor signs consists of structure and meaning shift.

Hak Disabilitas dalam Pelayanan Surat Izin Mengemudi pada Satlantas Polres Purbalingga

The right of persons with disabilities to obtain a driving license is a right that must be recognized and guaranteed to ensure accessibility and equality for everyone, including those with physical and mental limitations. In this regard, the government must ensure that the process of obtaining a driver's license is designed to be easily accessible and usable by everyone, including people with disabilities. In addition, the Government must provide special facilities and services that suit their needs, such as sign language interpreters or other tools to facilitate them. In accordance with the provisions of article 28 h of the Law of the Republic of Indonesia which states that everyone has the right to obtain special facilities and services to achieve equality and justice. The government should also provide clear information on the procedures for obtaining a driver's license that covers all types of disabilities, such as guidance on the technical requirements and application process that apply to them. This will ensure that they have sufficient knowledge and feel supported when processing an extension or new driver's license. This research aims to examine how disability protection in obtaining a driver's license for persons with disabilities is a right of all citizens who meet the requirements. This case concerns National Police Chief Regulation No. 9/2012 on Driver's License. In this case, the case study was conducted at the Purbalingga Police Traffic Division Office. The method used in this research is a normative legal method with an empirical juridical approach, namely interviews and observations in the Purbalingga Regency area, then analyzed qualitatively to see whether it is in accordance with the National Police Chief Regulation Number 9 of 2012. Based on this. the findings obtained. And it is concluded that the implementation of Purbalingga Police in issuing driving licenses for persons with disabilities based on the National Police Chief Regulation is quite good, although overall it is not good enough. However, the technical implementation in the field has not been able to adapt to the situation of persons with disabilities.

Enhancing Sign Language Understanding through Machine Learning at the Sentence Level

Abstract: The visual language of sign language is based on nonverbal communication, including hand and body gestures. When it comes to communicating, it is the main tool for those who are deaf or hard of hearing all around the globe. Useful for both hearing and deaf persons, this can translate sign language into sentences in real-time or help those who are hard of hearing communicate with others. This work focuses on developing a sentence-level sign language detection system utilizing a custom dataset and Random Forest model. Leveraging tools such as Media Pipe and TensorFlow, we facilitate gesture detection. Through continuous detection of gestures, we generate a list of corresponding labels. These labels are then used to construct sentences automatically. The system seamlessly integrates with ChatGPT, allowing direct access to generate sentences based on the detected gestures. Our custom dataset ensures that the model can accurately interpret a wide range of sign language gestures. Our method helps close the communication gap between people who use sign language and others, with an accuracy of 80%, by merging machine learning with complex language models.

Brokering understanding: Canadian deaf interpreters’ role and practice

ABSTRACT This article reports findings from semi-structured interviews with twelve Canadian deaf interpreter (DI) participants as part of a three-year study of language ideologies related to DIs. DIs are professional or amateur sign language interpreters and translators who are deaf and who may often but not always work as part of a team with hearing interpreters. When working with a hearing interpreter who uses the same national sign language, the DI’s role is often seen as meeting the needs of deaf clients who are viewed as lacking proficiency in a named language and/or who are viewed as monolingual in a named national sign language. This reflects normative language ideologies and conceptions of interpreting and translation. DI participants described their role in terms of their enhanced powers of understanding that elicited greater information from other deaf individuals than was apparent to a hearing interpreter. In addition, DI participants characterized their work as primarily translation, in a manner that accords with translation as the creation of meaning and as translanguaging that extends beyond named languages and deploys the individual’s full semiotic repertoire.

Alphabet Recognition of American Sign Language Using Machine Learning

A major challenge faced by our society is the difficulty individuals with disabilities encounter in expressing their emotions to others. People with disabilities often depend on sign (gesture) languages for communication. This project aims to develop a model capable of recognizing and translating sign language alphabets from hand gestures into text and audio. The primary objective is to enhance communication between individuals with hearing impairments and the broader society. We assessed our model's performance using a publicly accessible Indian Sign Language (ISL) dataset. For image classification, we employed Convolutional Neural Networks (CNNs) with the Inception V3 architecture. Hand gestures are captured through webcams, and our model identifies the corresponding alphabet for each gesture. This project seeks to overcome current challenges in Sign Language Recognition and aims to enhance its effectiveness and efficiency.

Artificial Intelligence Promoting the Inclusion of Students with Special Needs in Physical Education Classes

School Physical Education (PE), a crucial component for the integral development of students, faces the challenge of promoting the inclusion of students with special needs (SEN). Barriers such as the lack of adaptation of activities and the scarcity of adequate resources hinder the full participation of these students. This article investigates the potential of Artificial Intelligence (AI) as a tool to personalize teaching, adapt activities, and create inclusive learning environments in PE. Through the analysis of case studies and practical examples, it demonstrates how AI can be used to individually assess students, provide real-time feedback, develop adaptive platforms, recognize gestures and movements, create gamified activities, use virtual and augmented reality, translate sign language, implement virtual assistants, and prevent bullying. At the same time, the article discusses the ethical challenges and the need for teacher training to ensure the responsible and effective use of AI in promoting inclusion in PE.

Sworn Sign Language Interpreters Provision for Deaf People Appearing before Notary Based on Justice Principle

Sworn Sign Language Interpreters Provision for Deaf People Appearing before Notary Based on Justice Principle

Bridging the Gap: Exploring Translation Equivalence and Enhancing Public Sign Translations in Xuzhou's Tourism Spots

Bridging the Gap: Exploring Translation Equivalence and Enhancing Public Sign Translations in Xuzhou's Tourism Spots

Sign Tone: A Deep Learning-Based Deaf Companion System for Two Way Communication Between Deaf and Non-Deaf Individuals

Communication is essential to express and receive information, knowledge, ideas, and views among people, but it has been quite a while to be an obstruction for people with hearing and mute disabilities. Sign language is one method of communicating with deaf people. Though there is sign language to communicate with non-sign people it is difficult for everyone to interpret and understand. The performance of existing sign language recognition approaches is typically limited. Developing an assistive device that will translate the sign language to a readable format will help the deaf-mutes to communicate with ease to the common people. Recent advancements in the development of deep learning, deep neural networks, especially Temporal convolutional networks (TCNs) have provided solutions to the communication of deaf and mute individuals. In this project, the main objective is to design Deaf Companion System for that to develop SignNet Model to provide two-way communication of deaf individuals and to implement an automatic speaking system for deaf and mute people. It provides two-way communication for all classes of people (deaf-and-mute, hard of hearing, visually impaired, and non-signers) and can be scaled commercially. The proposed system, consists of three modules; the sign recognition module (SRM) that recognizes the signs of a deaf individual using TCN, the speech recognition using Hidden Marko Model and synthesis module (SRSM) that processes the speech of a non-deaf individual and converts it to text, and an Avatar module (AM) to generate and perform the corresponding sign of the non-deaf speech, which were integrated into the sign translation companion system called deaf companion system to facilitate the communication from the deaf to the hearing and vice versa. The proposed model is trained on Indian Sign Language. Then developed a web-based user interface to deploy SignNet Model for ease of use. Experimental results on MNIST sign language recognition datasets validate the superiority of the proposed framework. The TCN model gives an accuracy of 98.5%..

The Existence of Sign Language Interpreters in Assisting Deaf Individuals in the Creation of Notarial Deeds

The Existence of Sign Language Interpreters in Assisting Deaf Individuals in the Creation of Notarial Deeds

Attention-Based BiGRU Model for Real-time Sign Language Translation Applications

Sign language applications provide an important key to solving communication problems for deaf community and normal hearing people. Current research problem usually focuses on improving communication access between deaf and hearing people. In this study, we consider real-time communication context from deaf to hearing people, and thus we propose an attention-based bidirectional gated recurrent unit (A-BiGRU) model which demonstrates on trading-off among an precision performance, and computational efficiency which includes training time, testing time, and system resources on extended the American Sign Language Gloss (E-ASLG-PC12) dataset. The results shown that our proposal has a significant performance improvement in term of training time, testing time, system resources, comparing to attentionbased bidirectional long-short term memory (A-BiLSTM), and the other moderns of sequence to sequence models. Moreover, precision performance of our proposal model achieve closer to that of the complex architecture, A-BiLSTM. Thus, we believe that our proposed model is a suitable and potential candidate for real-time translation applications as well as and lower computational devices when they solve the communication problems from deaf to normal hearing people direction. Keywords– computational efficiency (CE), attention-based bidirectional gated recurrent unit (A-BiGRU), sign language translation applications (SLTA).

Legal Assistance for Deaf: Role of Indian Sign Language Digital Library

The digital library is the most widely used source of legal information. However, libraries in India do not fulfill their obligation to provide the deaf population with the necessary legal information and support. Libraries need to investigate different kinds of assistive technology, which could be a beneficial way to give the deaf population access to important legal information resources and help them deal with the problem. This article addresses the legal issues and challenges faced by the deaf population, the role of Indian sign language (ISL) interpreters in providing legal assistance, and the disadvantages of ISL interpreters in the legal system when providing legal services to the deaf population. To overcome the issues and challenges, this article focuses on the design and development of the ISL Legal Digital Library to support the deaf and the legal system.

Enhancing communication: Deep learning for Arabic sign language translation

Abstract This study explores the field of sign language recognition through machine learning, focusing on the development and comparative evaluation of various algorithms designed to interpret sign language. With the prevalence of hearing impairment affecting millions globally, efficient sign language recognition systems are increasingly critical for enhancing communication for the deaf and hard-of-hearing community. We review several studies, showcasing algorithms with accuracies ranging from 63.5 to 99.6%. Building on these works, we introduce a novel algorithm that has been rigorously tested and has demonstrated a perfect accuracy of 99.7%. Our proposed algorithm utilizes a sophisticated convolutional neural network architecture that outperforms existing models. This work details the methodology of the proposed system, which includes preprocessing, feature extraction, and a multi-layered CNN approach. The remarkable performance of our algorithm sets a new benchmark in the field and suggests significant potential for real-world application in assistive technologies. We conclude by discussing the impact of these findings and propose directions for future research to further improve the accessibility and effectiveness of sign language recognition systems.

SCIENTIFIC ASPECTS OF MODERN APPROACHES TO MACHINE TRANSLATION FOR SIGN LANGUAGE

Scientific research in the field of automated sign language translation represents a crucial stage in the development of technologies supporting the hearing-impaired and deaf communities. This article presents a comprehensive approach to addressing semantic and technical challenges associated with the uniqueness of sign language. The research goal is to create an innovative system that combines semantic analysis, sign synthesis, and facial mimicry for the most accurate conveyance of emotional context. The study focuses on the unique features of the Kazakh language and cultural contexts that influence sign communication. The research centers on the development of a semantic system capable of adequately interpreting metaphors, idioms, and classifier predicates of sign language. The three-dimensional nature of signs is analyzed, and a solution to the formal description problem is proposed. The article introduces a database, analysis algorithm, and a prototype 3D avatar capable of translating textual data into sign language. Special attention is given to the processing of idioms and variability in expressing emotions in sign language. Utilizing machine learning principles and computational linguistics algorithms, the authors present an integrated approach to sign language translation, considering linguistic, cultural, and emotional aspects. The proposed algorithms and formulas facilitate effective interaction between textual information and sign expression. The research results not only provide an overview of current challenges in automated sign language translation but also offer practical approaches to addressing them. The developed approach could be a key step towards creating more efficient communication systems for the hearing-impaired and deaf. Which in the future may solve numerous issues with Kazakh sign language.

Linguistic Landscape Analysis of Identity Representation in Public Signs at Watugong Buddhist Monastery Semarang

Public signs at Watugong Monastery in Semarang serve not only as guides for visitors but also as representations of identity, meaning, and values. This study aims to uncover the meaning and representation of identity in the public signs of Watugong Monastery by considering the cultural, religious, and social contexts in accordance with the dominant ideology in the place. This study uses a qualitative descriptive method with a Barthes (1991) semiotics approach. Research data was collected through observation and documentation methods using photography techniques. The results of this study show that there are representations of cultural, religious, and socio-religious identities in the Public signs of Watugong Monastery. Religious identity comes from the interpretation of the object label signs 福 (fú), 祿 (lù), and 壽 (shòu) which reflect Chinese cultural values. Religious identity emerges from hiolo stick sign, which contains the meaning of strong faith in Buddha and his teachings through prayer and devotion supported by morality and exemplary behavior. Finally, socio-religious identity appears on the Ashoka inscription sign, the strong religious element derived from Buddhist teachings, the inscription also shows an example of social life between people of different faiths who must always teach tolerance and moderation in religion. This research is still very open for further research in various other aspects of LL, for example, visitors' perceptions of the language used at Watugong Monastery.

Dificultades en la interpretación y su influencia en las preferencias de direccionalidad de las intérpretes de lengua de signos española (ILSE)

Directionality preferences in interpreting is a controversial topic for the academic and professional community, which questions which direction requires less effort and produces higher quality interpreting. In the case of oral language interpreters, it is suggested that the least difficult, accurate and preferred direction is towards the mother tongue. However, in signed languages, studies show the opposite preference, even though the professionals consider themselves to be less proficient and competent in sign language. With this non-experimental study with an exploratory-descriptive scope, we intend to find out the directionality preferences of Spanish sign language interpreters (ILSE) and the factors that condition them. A self-administered questionnaire was used in which 101 ILSE participated. The results suggest that professionals prefer and perceive a higher quality of interpretation into sign language, despite having acquired it as a second language and declaring themselves less competent. Among the factors that condition them, training, experience, and perceived difficulties in direct interpreting stand out. However, after this first approximation, we consider that it would be necessary to analyze the real difficulties of each interpreting direction and their impact on performance.