Academic literature on the topic 'Korean Sign Language'

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Journal articles on the topic "Korean Sign Language"

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Lim, Ji-Ryong, and Hyunju Song. "Motivation in Korean Sign Language." Korean Semantics 49 (September 30, 2015): 59. http://dx.doi.org/10.19033/sks.2015.09.49.59.

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Nam, Kihyun, and JunMo Cho. "Anaphoric Expressions of Korean Sign Language." Korean Semantics 62 (December 31, 2018): 133–58. http://dx.doi.org/10.19033/sks.2018.12.62.133.

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Nam, Ki-Hyun, Yeon-Woo Kim, and Jun-Mo Cho. "Agreement Phenomena in Korean Sign Language." Korean Semantics 65 (September 30, 2019): 75–107. http://dx.doi.org/10.19033/sks.2019.9.65.75.

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Yang, Seon Ah, and Youngju Choi. "Universality in Meanings of Handshapes: Focusing on Hand-Opening Signs in Korean Sign Language." Studies in Modern Grammar 116 (December 24, 2022): 149–70. http://dx.doi.org/10.14342/smog.2022.116.149.

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Cabeza-Pereiro (2014) identifies the meanings of hand-opening signs in Spanish Sign Language (LSE) and British Sign Language (BSL) as ‘to disappear’ and ‘to appear.’ The purpose of this paper is to observe the same hand-opening signs in Korea Sign Language (KSL) and find out whether they have the same meanings as analyzed in LSE and BSL. The close examination of 294 signs with hand-opening articulation in KSL demonstrates that they similarly have the two meanings, ‘to disappear’ and ‘to appear’ and, in addition, it has the meanings of ‘to spread’ and ‘to deliver.’ The result supports universality in meanings of handshapes in sign languages.
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Na, Youngmin, Hyejin Yang, and Jihwan Woo. "Classification of the Korean Sign Language Alphabet Using an Accelerometer with a Support Vector Machine." Journal of Sensors 2021 (August 12, 2021): 1–10. http://dx.doi.org/10.1155/2021/9304925.

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Recognition and understanding of sign language can aid communication between nondeaf and deaf people. Recently, research groups have developed sign language recognition algorithms using multiple sensors. However, in everyday life, minimizing the number of sensors would still require the use of a sign language interpreter. In this study, a sign language classification method was developed using an accelerometer to recognize the Korean sign language alphabet. The accelerometer is worn on the proximal phalanx of the index finger of the dominant hand. Triaxial accelerometer signals were used to segment the sign gesture (i.e., the time period when a user is performing a sign) and recognize the 31 Korean sign language letters (producing a chance level of 3.2%). The vector sum of the accelerometer signals was used to segment the sign gesture with 98.9% segmentation accuracy, which is comparable to that of previous multisensor systems (99.49%). The system was able to classify the Korean sign language alphabet with 92.2% accuracy. The recognition accuracy of this approach was found to be higher than that of a previous work in the same sign language alphabet classification task. The findings demonstrate that a single-sensor accelerometer with simple features can be reliably used for Korean sign language alphabet recognition in everyday life.
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Ahn, Young-Hoe. "Feature of Korean Sign Language and Practice of the Sign Language Bible Translation." Journal of Biblical Text Research 25 (October 31, 2009): 149–70. http://dx.doi.org/10.28977/jbtr.2009.10.25.149.

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남기현. "Verbal Classifiers in Korean Sign Language (KSL)." Journal of Studies in Language 24, no. 4 (February 2009): 707–30. http://dx.doi.org/10.18627/jslg.24.4.200902.707.

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Nam, Ki-Hyun. "Adjectives and order in Korean Sign Language." Journal of special education : theory and practice 17, no. 3 (July 30, 2016): 211–35. http://dx.doi.org/10.19049/jsped.2016.17.3.09.

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Shin, Jungpil, Abu Saleh Musa Miah, Md Al Mehedi Hasan, Koki Hirooka, Kota Suzuki, Hyoun-Sup Lee, and Si-Woong Jang. "Korean Sign Language Recognition Using Transformer-Based Deep Neural Network." Applied Sciences 13, no. 5 (February 27, 2023): 3029. http://dx.doi.org/10.3390/app13053029.

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Sign language recognition (SLR) is one of the crucial applications of the hand gesture recognition and computer vision research domain. There are many researchers who have been working to develop a hand gesture-based SLR application for English, Turkey, Arabic, and other sign languages. However, few studies have been conducted on Korean sign language classification because few KSL datasets are publicly available. In addition, the existing Korean sign language recognition work still faces challenges in being conducted efficiently because light illumination and background complexity are the major problems in this field. In the last decade, researchers successfully applied a vision-based transformer for recognizing sign language by extracting long-range dependency within the image. Moreover, there is a significant gap between the CNN and transformer in terms of the performance and efficiency of the model. In addition, we have not found a combination of CNN and transformer-based Korean sign language recognition models yet. To overcome the challenges, we proposed a convolution and transformer-based multi-branch network aiming to take advantage of the long-range dependencies computation of the transformer and local feature calculation of the CNN for sign language recognition. We extracted initial features with the grained model and then parallelly extracted features from the transformer and CNN. After concatenating the local and long-range dependencies features, a new classification module was applied for the classification. We evaluated the proposed model with a KSL benchmark dataset and our lab dataset, where our model achieved 89.00% accuracy for 77 label KSL dataset and 98.30% accuracy for the lab dataset. The higher performance proves that the proposed model can achieve a generalized property with considerably less computational cost.
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Kwak, Jeongran. "Sign Language Education as Cognitive Academic Language: Focusing on the ‘Japanese Sign Language(JSL)’ Curriculum and Textbooks of Meisei Gakuen in Japan." Korean Association For Learner-Centered Curriculum And Instruction 22, no. 20 (October 31, 2022): 611–29. http://dx.doi.org/10.22251/jlcci.2022.22.20.611.

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Objectives The purpose of this study is to present implications for deaf education of Korea by analyzing the ‘Japanese Sign Language(JSL)’ curriculum and textbooks of Meisei Gakuen in Japan, which provides bilingual and bicultural deaf education from the perspective of cognitive academic language. Methods For this purpose, the characteristics of Meisei Gakuen's kindergarten, elementary, and middle school ‘JSL’ curriculum and textbooks were analyzed from the perspective of cognitive academic language. Results First, the ‘JSL’ curriculum in kindergarten was designed to develop sign language skills as a basic communicative skills by considering the differences in sign language proficiency of deaf children. Sign language textbooks were designed to develop a sense of language for sign language through sign shapes cards and classifier textbooks. Second, the elementary school ‘JSL’ curriculum was designed to comprehensively develop the cognitive academic sign language ability in linguistic, cognitive, and socio-cultural aspects. Sign language textbooks are structured to systematically develop deaf culture and sign language’s grammar. Third, the ‘JSL’ curriculum of the middle school was structured to deepen the cognitive academic sign language ability in linguistic, cognitive, and socio-cultural aspects. Sign language textbooks were designed to deepen awareness of sign language by learning sign language linguistics. Fourth, as a limitation, there was an aspect that the sign language curriculum and sign language textbooks did not sufficiently consider the level difference by age and grade. Conclusions The direction of the development of the cognitive academic sign language curriculum for using Korean sign language as a teaching-learning language was suggested.
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Books on the topic "Korean Sign Language"

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Han'guk suhwa: Korea sign language. Sŏul T'ŭkpyŏlsi: Hakjisa, 2008.

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Ki-hyŏn, Nam, ed. Han'guk suŏhak kaeron: Introduction to Korean Sign Language linguistics. Kyŏnggi-do P'aju-si: Nanam, 2014.

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Han'guk suhwa. Sŏul T'ŭkpyŏlsi: Saenggak Shwimp'yo, 2014.

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Han'guk P'yojun Suhwa Kyubŏm Chejŏng Ch'ujin Wiwŏnhoe. Han'guk suhwa. Sŏul-si: Kungnip Kugŏwŏn, 2010.

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author, Kim Ch'il-gwan, ed. Han'guk suhwa ŏnŏhak immun. Kyŏnggi-do P'aju-si: Yangsŏwŏn, 2022.

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Kim, Sam-chʻan. Hanʼguk suhwa sajŏn. Sŏul Tʻŭkpyŏsi: Hyŏngsŏl Chʻulpʻansa, 2005.

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Suhwa ro hanŭn aegukka, kukki e taehan maengse, Han'gŭllal norae. Sŏul T'ŭkpyŏlsi: Hyumŏn K'ŏlch'ŏ Arirang, 2014.

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Nongin ŭi sam kwa suhwa ŏnŏ. Kyŏnggi-do P'aju-si: Nanam, 2020.

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Ch'ŏngdong ŭi sigan, kamja ŭi sigan: Hŏ Su-gyŏng sijip. Sŏul: Munhak kwa Chisŏngsa, 2005.

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Kŭndae Han'gugŏ sigi ŭi ŏnŏgwan, munchagwan yŏn'gu: A study on the perspectives of language and letters in modern Korean period. Sŏul-si: Somyŏng Ch'ulp'an, 2014.

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Book chapters on the topic "Korean Sign Language"

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Hong, Sung-Eun, Hyunhwa Lee, Mi-Hye Lee, and Seung-Il Byun. "2. The Korean Sign Language Act." In TheLegal Recognition of Sign Languages, edited by Maartje De Meulder, Joseph J. Murray, and Rachel L. McKee, 36–51. Bristol, Blue Ridge Summit: Multilingual Matters, 2019. http://dx.doi.org/10.21832/9781788924016-004.

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Yang, Seunghan, Seungjun Jung, Heekwang Kang, and Changick Kim. "The Korean Sign Language Dataset for Action Recognition." In MultiMedia Modeling, 532–42. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37731-1_43.

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Kim, Jung-Hyun, and Kwang-Seok Hong. "An Implementation of the Korean Sign Language Recognizer Using Neural Network Based on the Post PC." In Advances in Neural Networks - ISNN 2006, 222–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11760023_33.

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Sagara, Keiko. "Historical relationships between numeral signs in Japanese Sign Language, South Korean Sign Language and Taiwan Sign Language." In East Asian Sign Linguistics, 5–36. De Gruyter, 2022. http://dx.doi.org/10.1515/9781501510243-002.

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Nam, Ki-Hyun, and Kang-Suk Byun. "Classifiers and gender in Korean Sign Language." In East Asian Sign Linguistics, 71–100. De Gruyter, 2022. http://dx.doi.org/10.1515/9781501510243-004.

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Hong, Sung-Eun, Seong Ok Won, Hyunhwa Lee, Kang-Suk Byun, and Eun-Young Lee. "The Korean Sign Language (KSL) corpus and its first application on a study about mouth actions." In East Asian Sign Linguistics, 169–202. De Gruyter, 2022. http://dx.doi.org/10.1515/9781501510243-007.

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Korkealehto, Kirsi, and Maarit Ohinen-Salvén. "Finnish students’ perceptions of key elements in effective online language courses: insights from the KiVAKO project." In CALL for widening participation: short papers from EUROCALL 2020, 167–71. Research-publishing.net, 2020. http://dx.doi.org/10.14705/rpnet.2020.48.1183.

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This study explored Finnish students’ perceptions of online language courses with the KiVAKO project (KiVAKO is an acronym in Finnish meaning strengthening the language capital at higher education institutions). The aim was to identify and make visible the aspects that need to be taken into account in designing an effective online language course. The research context included eight pilot courses created and implemented within the framework of the KiVAKO project, which seeks to develop a nationwide online language course offering. Language instruction is offered in Chinese, Estonian, Finnish Sign Language, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish on Common European Framework of Reference (CEFR) levels A1-C1. The research data consisted of responses to a post-course online questionnaire. The data were analysed according to a qualitative content analysis method. The findings indicate that clearly structured course design, relevant learning materials, appropriate teacher activities, and aligned assignments enhanced the students’ positive learning experiences.
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Garrido-Nag, Karen, and James McCann. "Working With Deaf and Hard-of-Hearing Children From Linguistically Diverse Backgrounds." In Advances in Linguistics and Communication Studies, 157–79. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2261-5.ch008.

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An increasing number of deaf and hard-of-hearing (D/HH) children live in homes where languages other than English or American Sign Language (ASL) are used. This chapter reviews issues of culture and linguistic diversity when working with D/HH multilingual learners (DMLs) from identification and early intervention through school entry. The authors will provide two case studies to explore the issues of service delivery to DMLs and their families: 1) Ji-Hun, who appears to use several spoken languages, including Korean, Japanese, and English, and 2) Ana, who is a recent immigrant to the USA and appears to use ASL, spoken Spanish, and spoken English. The discussion of these two case studies will encompass some cultural differences, including 1) openness to engagement with providers, 2) cultural beliefs about hearing loss, 3) community systems and familiar support, 4) perceptions of systems and authorities. The case studies presented are not based on actual clients but are drawn from the clinical experiences of the authors.
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Oka, Norie. "Japanese Sign Language." In Language Communities in Japan, 59–67. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780198856610.003.0006.

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Japanese Sign Language (JSL or Nihon Shuwa) is an indigenous language of deaf people in Japan. It has regional dialects, generational and stylistic varieties. The lexico-grammatical structure of JSL shares similarities—and some mutual intelligibility—with the sign languages of Taiwan and Korea. JSL developed when deaf people started to form communities following the establishment of deaf schools in Japan in the 1880s. However, the use of sign language was not approved in deaf schools until the 1980s. In 2016, 31,000 persons out of 341,000 persons with hearing disabilities in Japan used signed language for daily communication. There are numerous non-deaf users of JSL as a first language, such as children of deaf adults (CODA). With the increase in the number of people undergoing cochlear implantation, the number of students in deaf schools is decreasing along with the number of native JSL signers.
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Feriani, Rim, Jasmina Bolfek-Radovani, and Debra Kelly. "Reading Signs and Symbols with Abdelkébir Khatibi." In Abdelkébir Khatibi, 237–60. Liverpool University Press, 2020. http://dx.doi.org/10.3828/liverpool/9781789622331.003.0011.

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This chapter considers the ways in which Khatibi’s practices of reading contribute to theories of meaning through his thinking on the deciphering of signs and symbols and of making sense of the world, and of the worlds of the text, in their multifaceted forms. It takes as its starting point what Khatibi terms, in his introductory essay ‘Le Cristal du Texte’ in La Bessure du Nom propre, ‘l’intersémiotique’, migrant signs which move between one sign system and another. Khatibi takes as his own project examples from semiotic systems found within Arabic and Islamic cultures, from both popular culture, such as the tattoo, to calligraphy and the language of the Koran, from the body to the text and beyond – including storytelling, mosaics, urban space, textiles. His readings reveal the intersemiotic and polysemic meanings created in the movements of these migrant signs between their sign systems. For Khatibi, this ‘infinity’ of the ‘text’ is linked also to a mobile and migrant identity refracted in the multifaceted surfaces of the crystal (hence the title of the essay – ‘Le Cristal du Texte’) rather than in one reflection as in a mirror. Moving from these concerns of Khatibi with which he develops his radical theory of the sign, of the word and of writing, the chapter goes on to propose new readings of a selection of other writers with a shared, but varied, relationship to their Islamic heritage. These are writers working with and through that heritage – and importantly, as for Khatibi, including the Sufi heritage – and whose writing is also resonant with Khatibi’s intersemiotic theoretical and cultural project concerned with the individual and the collective, the historical and the contemporary, the political, the social and the linguistic.
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Conference papers on the topic "Korean Sign Language"

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Caliwag, Angela, Stephen Ryan Angsanto, and Wansu Lim. "Korean Sign Language Translation Using Machine Learning." In 2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN). IEEE, 2018. http://dx.doi.org/10.1109/icufn.2018.8436747.

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Kim, Minho, Sung-ki Choi, Aesun Yoon, and Hyuk-Chul Kwon. "Practical Target Word Selection Method in Korean to Korean Sign Language Machine Translation." In 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM). IEEE, 2015. http://dx.doi.org/10.1109/cit/iucc/dasc/picom.2015.140.

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Kim, San, Chang Jo Kim, Han-Mu Park, Yoonyoung Jeong, Jin Yea Jang, and Hyedong Jung. "Robust Keypoint Normalization Method for Korean Sign Language Translation using Transformer." In 2020 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2020. http://dx.doi.org/10.1109/ictc49870.2020.9289551.

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Shin, Hyojoo, Woo Je Kim, and Kyoung-ae Jang. "Korean sign language recognition based on image and convolution neural network." In the 2nd International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3313950.3313967.

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Hong, Mun-Ho, Chang-Seok Choi, Chang-Seok Kim, and Joon-Hyeon Jeon. "Synthesis of image sequences for Korean sign language using 3D shape model." In High-Speed Photography and Photonics: 21st International Congress, edited by Ung Kim, Joon-Sung Chang, and Seung-Han Park. SPIE, 1995. http://dx.doi.org/10.1117/12.209654.

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Kim, Jung-hyun, and Kwang-seok Hong. "An Extended CSCW Architecture Using Wearable Personal Station-Based Korean Sign Language Recognizer." In 2006 10th International Conference on Computer Supported Cooperative Work in Design. IEEE, 2006. http://dx.doi.org/10.1109/cscwd.2006.253023.

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Shin, Seongjoo, Youngmi Baek, Jinhee Lee, Yongsoon Eun, and Sang Hyuk Son. "Korean sign language recognition using EMG and IMU sensors based on group-dependent NN models." In 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2017. http://dx.doi.org/10.1109/ssci.2017.8280908.

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Ham, Soomin, Kibaek Park, YeongJun Jang, Youngtaek Oh, Seokmin Yun, Sukwon Yoon, Chang Jo Kim, Han-Mu Park, and In So Kweon. "KSL-Guide: A Large-scale Korean Sign Language Dataset Including Interrogative Sentences for Guiding the Deaf and Hard-of-Hearing." In 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021). IEEE, 2021. http://dx.doi.org/10.1109/fg52635.2021.9667011.

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