Relevant bibliographies by topics / Sign Language (SL)

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Academic literature on the topic 'Sign Language (SL)'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Sign Language (SL)"

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., Sriramkumar, Pavan Kalayan, Harsha J, and Yashwanth K. "Sign Language Translator." International Research Journal of Computer Science 10, no. 05 (2023): 264–67. http://dx.doi.org/10.26562/irjcs.2023.v1005.28.

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The deaf community in India relies heavily on the Sign Language (SL) as a means of communication. But because so few people are fluent in SL, there is a communication gap between the hearing and deaf communities. The Sign Language Translator (SLT) in this paper employs MediaPipe and LSTM to convert Sign Language (SL) to text and back again. The suggested approach first uses MediaPipe to extract hand movements and facial emotions from movies of SL signals. The LSTM model, which is trained using a sizable dataset of SL signs and their related text labels, is then fed these characteristics. The i
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Subin M. Varghese and K. Aravinthan. "A robust finger detection based sign language recognition using pattern recognition techniques." Scientific Temper 15, spl-1 (2024): 247–53. https://doi.org/10.58414/scientifictemper.2024.15.spl.29.

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Sign language recognition based on finger detection is arguably the main sign language used by most dumb people. It has its own phonetics, grammar and syntax that set it apart from other sign languages. Research related to sign language (SL) is only now becoming standardized. Considering the challenge of recognizing SL, in this work a new method for recognizing SL dynamic gestures is proposed. Sign language (SL) translation systems can be used to help dumb people interact with normal people with the help of a computer. Most studies on continuous recognition of sign language are done by process
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Schwager, Waldemar, and Ulrike Zeshan. "Word classes in sign languages." Parts of Speech: Descriptive tools, theoretical constructs 32, no. 3 (2008): 509–45. http://dx.doi.org/10.1075/sl.32.3.03sch.

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The topic of word classes remains curiously under-represented in the sign language literature due to many theoretical and methodological problems in sign linguistics. This article focuses on language-specific classifications of signs into word classes in two different sign languages: German Sign Language and Kata Kolok, the sign language of a village community in Bali. The article discusses semantic and structural criteria for identifying word classes in the target sign languages. On the basis of a data set of signs, these criteria are systematically tested out as a first step towards an induc
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Qadhi, Omaimah. "Sign language use in healthcare: professionals’ insight." PeerJ 13 (June 2, 2025): e19446. https://doi.org/10.7717/peerj.19446.

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Background and Aim Communication using sign language (SL) between health care providers (HCPs) and deaf and/or hearing-impaired (DHI) patients was reported to be difficult and oftentimes results in a compromised delivery of quality health care to patients. This study surveyed Saudi health care providers on their perception of SL knowledge on the provision of high-quality care to DHI patients. Methods This was a cross-sectional descriptive study among HCPs in different health and primary care centers in Riyadh, Saudi Arabia. The questionnaire was distributed officially by the Department of Surv
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M, Prema, and Gomathi P M. "ANALYSIS ON DIFFERENT METHODS FOR SIGN LANGUAGE IDENTIFICATION." ICTACT Journal on Soft Computing 12, no. 2 (2022): 2567–71. http://dx.doi.org/10.21917/ijsc.2022.0367.

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Sign Language (SL) is the most organized and structured type of hand/arm gesture in the communicative hand/arm gesture taxonomies. The ability of machines to comprehend human actions and meanings has numerous uses. SL identification is one area of focus. SL is employed by the deaf and hard-of-hearing communities to communicate. Hearing-impaired persons communicate via visual indicators instead of vocal communication and sound patterns. SL also uses facial expressions and body postures as a medium of communication. Pattern matching, computer vision, natural language processing are the key facto
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Adamyuk, Natalia. "Contribution of Deaf Researchers of Ukraine to the Development of the National Sign Language." Kadmos 8 (2016): 465–76. https://doi.org/10.32859/kadmos/8/465-476.

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The paper traces the development of the Ukrainian National Sign Language. It highlights the challenges relating to the introduction and application of national sign languages in former Soviet republics, and gives an account of the painstaking activities of the Ukrainian Society of the Deaf and the Sign Language Laboratory. The SL Laboratory, which includes deaf members as well as members belonging to deaf families, widely engages in research, USL teaching and teacher training. It organizes regular nationwide conferences on SL issues and actively collaborates with local, regional and internatio
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Lepp, Lisa, Dimitar Shterionov, Mirella De Sisto, and Grzegorz Chrupała. "Co-Creation for Sign Language Processing and Translation Technology." Information 16, no. 4 (2025): 290. https://doi.org/10.3390/info16040290.

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Sign language machine translation (SLMT)—the task of automatically translating between sign and spoken languages or between sign languages—is a complex task within the field of NLP. Its multi-modal and non-linear nature require the joint efforts of sign language (SL) linguists, technical experts, and SL users. Effective user involvement is a challenge that can be addressed through co-creation. Co-creation has been formally defined in many fields, e.g., business, marketing, educational, and others; however, in NLP and in particular in SLMT, there is no formal, widely accepted definition. Starti
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Mertzani, Maria. "SIGN LANGUAGE LITERACY IN THE SIGN LANGUAGE CURRICULUM." Momento - Diálogos em Educação 31, no. 02 (2022): 449–74. http://dx.doi.org/10.14295/momento.v31i02.14504.

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The Sign Language curriculum is a contemporary development which few countries have officially implemented to teach a national standard Sign Language as a first language (L1) and/or mother tongue in the school grades. In these, Sign Language is a mandatory unit, which the deaf child needs to study and develop metalinguistically, as is the case in learning spoken languages as L1. A Sign Language as a metalanguage also means that the curriculum teaches explicit linguistic knowledge for the child to understand gradually how SL functions in different contexts, to make effective choices for meaning
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Naranjo-Zeledón, Luis, Mario Chacón-Rivas, Jesús Peral, and Antonio Ferrández. "Architecture design of a reinforcement environment for learning sign languages." PeerJ Computer Science 7 (October 12, 2021): e740. http://dx.doi.org/10.7717/peerj-cs.740.

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Different fields such as linguistics, teaching, and computing have demonstrated special interest in the study of sign languages (SL). However, the processes of teaching and learning these languages turn complex since it is unusual to find people teaching these languages that are fluent in both SL and the native language of the students. The teachings from deaf individuals become unique. Nonetheless, it is important for the student to lean on supportive mechanisms while being in the process of learning an SL. Bidirectional communication between deaf and hearing people through SL is a hot topic
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Ryumin, D., D. Ivanko, and A. Axyonov. "CROSS-LANGUAGE TRANSFER LEARNING USING VISUAL INFORMATION FOR AUTOMATIC SIGN GESTURE RECOGNITION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W3-2023 (May 12, 2023): 209–16. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-w3-2023-209-2023.

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Abstract. Automatic sign gesture recognition (GR) plays a critical role in facilitating communication between hearing-impaired individuals and the rest of society. However, recognizing sign gestures accurately and efficiently remains a challenging task due to the diversity of sign languages (SLs) and their limited availability of labeled data. This scientific paper proposes a new approach to improving the accuracy of automatic sign GR using cross-language transfer learning with visual information. Two large-scale multimodal SL corpora are utilized as the basic SLs for this study: the Ankara Un
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Book chapters on the topic "Sign Language (SL)"

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Efthimiou, Eleni, Stavroula-Evita Fotinea, Christina Flouda, et al. "The SL-ReDu Environment for Self-monitoring and Objective Learner Assessment in Greek Sign Language." In Lecture Notes in Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78095-1_7.

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Milković, Marina, and Ronnie Wilbur. "Agreement marking in Croatian Sign Language." In Angles of Object Agreement. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192897749.003.0008.

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Abstract We argue that failure to accurately identify sign components led to misconceptions that sign languages (SLs) violate generalizations about spoken-language verb agreement. Because it was assumed that verb phonological path movement (from location A to location B) carried agreement information, it was claimed that (1) only a subset of verbs shows agreement, leading to search for triggers; and (2) object agreement is more common, with subject agreement visible when object is marked. We argue, following Lourenço (2018), that when locations themselves are recognized as marking agreement wi
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Rajasekar, Elakkiya, Archana Mathiazhagan, and Elakkiya Rajalakshmi. "Hybrid Convolutional Recurrent Neural Network for Isolated Indian Sign Language Recognition." In Deep Learning: Theory, Architectures and Applications in Speech, Image and Language Processing. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815079210123010012.

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Even though the hearing and vocally impaired populace rely entirely on Sign Language (SL) as a way of communication, the majority of the worldwide people are unable to interpret it. This creates a significant language barrier between these two categories. The need for developing Sign Language Recognition (SLR) systems has arisen as a result of the communication breakdown between the deaf-mute and the general populace. This paper proposes a Hybrid Convolutional Recurrent Neural Network-based (H-CRNN) framework for Isolated Indian Sign Language recognition. The proposed framework is divided into
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Conference papers on the topic "Sign Language (SL)"

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Fink, Jérôme, Pierre Poitier, Maxime André, et al. "Sign Language-to-Text Dictionary with Lightweight Transformer Models." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/662.

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The recent advances in deep learning have been beneficial to automatic sign language recognition (SLR). However, free-to-access, usable, and accessible tools are still not widely available to the deaf community. The need for a sign language-to-text dictionary was raised by a bilingual deaf school in Belgium and linguist experts in sign languages (SL) in order to improve the autonomy of students. To meet that need, an efficient SLR system was built based on a specific transformer model. The proposed system is able to recognize 700 different signs, with a top-10 accuracy of 83%. Those results ar
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Papadimitriou, Katerina, Galini Sapountzaki, Kyriaki Vasilaki, Eleni Efthimiou, Stavroula-Evita Fotinea, and Gerasimos Potamianos. "SL-REDU GSL: A Large Greek Sign Language Recognition Corpus." In 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW). IEEE, 2023. http://dx.doi.org/10.1109/icasspw59220.2023.10193306.

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Zheng, Junru, Sihan Liang, Shun Zhang, Gaofei Sun, and Shengrong Gong. "Wi-SL: A Cross-Domain Sign Language Recognition System Based on Re-sidual Convolutional Networks." In The 13th IIAE International Conference on Industrial Application Engineering 2025. The Institute of Industrial Applications Engineers, 2025. https://doi.org/10.12792/iciae2025.033.

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Sapountzaki, Galini, Eleni Efthimiou, Stavroula-Evita Fotinea, Katerina Papadimitriou, and Gerasimos Potamianos. "3D GREEK SIGN LANGUAGE CLASSIFIERS AS A LEARNING OBJECT IN THE SL-REDU ONLINE EDUCATION PLATFORM." In 14th International Conference on Education and New Learning Technologies. IATED, 2022. http://dx.doi.org/10.21125/edulearn.2022.1449.

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