• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.688-702
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• 1998

In this paper, we propose sign language morpheme generation rule corresponding to morpheme analysis for each part of speech. Korean natural sign language has extremely limited vocabulary, and the number of grammatical components eing currently used are limited, too. In this paper, therefore, we define natural sign language grammar corresponding to Korean language grammar in order to translate natural Korean language sentences to the corresponding sign language. Each phrase should define sign language morpheme generation grammar which is different from Korean language analysis grammar. Then, this grammar is applied to morpheme analysis/combination rule and sentence structure analysis rule. It will make us generate most natural sign language by definition of this grammar.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.27-32
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• 2008

Sign languages, commonly used in aurally challenged communities, are a kind of visual language expressing sign words with motion. Spatiality and motility of a sign language are conveyed mainly via sign words as predicates. A predicate is modified by an adverbial phrase with an accompanying change in its semantics so that the adverbial phrase can also affect the overall spatiality and motility of expressions of a sign language. In this paper, we analyze the semantic features of adverbial phrases which may affect the motion-related semantics of a predicate in converting expressions in Korean into those in a sign language and propose a system that generates corresponding animation by utilizing these features.

• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.664-675
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• 2019

This study examined Korean sign Language of the linguistic form and the etymological forms about the origins of the Korean national sign languages. The general sign language has been shown through previous research all of place names from Chinese character except Seoul and Lmsil. And then, Sign language's form and origins which are current using in order to examine what kind of feature were analysed through interviews and publications in Korean association of the deaf people. As a result, it was analysed that was composed majority. indigenous sign language Korean place names were made and used by deaf than loan word character of Chinese characters, Hangul and loanword. When we consider that place names were correspond to a precious cultural heritage, representing the history with the culture and identity of the relevant area, we can worth of preservation and transmission to the abundant iconicity in the name of Sui. On the other hand the indigenous sign language korea place manes can worth deaf culture or korean sign language. Even lf geographical characteristics of area have been changed or local product was disappeared in this situation by The origin of sign language reach in modern time local specialty by geographical form lt continued over generation. This can be regarded as the Korean sign language of the form in the way of visual. lt will be very valuable heritage in the preservation deaf culture.

• Smart Media Journal
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• v.12 no.1
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• pp.32-46
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• 2023

Natural Language Processing (NLP) has grown tremendously in recent years. Typically, bilingual, and multilingual translation models have been deployed widely in machine translation and gained vast attention from the research community. On the contrary, few studies have focused on translating between spoken and sign languages, especially non-English languages. Prior works on Sign Language Translation (SLT) have shown that a mid-level sign gloss representation enhances translation performance. Therefore, this study presents a new large-scale Korean sign language dataset, the Museum-Commentary Korean Sign Gloss (MCKSG) dataset, including 3828 pairs of Korean sentences and their corresponding sign glosses used in Museum-Commentary contexts. In addition, we propose a translation framework based on self-supervised learning, where the pretext task is a text-to-text from a Korean sentence to its back-translation versions, then the pre-trained network will be fine-tuned on the MCKSG dataset. Using self-supervised learning help to overcome the drawback of a shortage of sign language data. Through experimental results, our proposed model outperforms a baseline BERT model by 6.22%.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.216-218
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• 2007

Korean Sign Language (KSL) is a communication method for the Deaf in Korea, and hand shape is one of important elements in sign language. In this paper, we developed a KSL hand shape editor to simply compose hand shape and connect it to a database. We can edit hand shape by a graphical user interface (GUI) on 3D virtual reality environment. Hand shape codes are connected to a sign word editor to synthesize sign motion and to decrease total amount of KSL data.

• Language and Information
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• v.10 no.1
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• pp.71-91
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• 2006

The linguistic characteristics of a sign language provide an important clue for an automatic construction of its expression from a given natural language sentence. For such characterization, we focus on the identification of elided constituents, the mapping of property-changing information into spatio-temporal dimension, and the need for rearranging the order of component information for enhanced quality of delivery. We use our characterization to implement a system that converts sentences in Korean into corresponding expressions in the Korean Sign Language.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.82-91
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• 2009

Sign language spotting is the task of detecting and recognizing the signs in a signed utterance. The difficulty of sign language spotting is that the occurrences of signs vary in both motion and shape. Moreover, the signs appear within a continuous gesture stream, interspersed with transitional movements between signs in a vocabulary and non-sign patterns(which include out-of-vocabulary signs, epentheses, and other movements that do not correspond to signs). In this paper, a novel method for designing a threshold model in a conditional random field(CRF) model is proposed. The proposed model performs an adaptive threshold for distinguishing between signs in the vocabulary and non-sign patterns. A hand appearance-based sign verification method, a short-sign detector, and a subsign reasoning method are included to further improve sign language spotting accuracy. Experimental results show that the proposed method can detect signs from continuous data with an 88% spotting rate and can recognize signs from isolated data with a 94% recognition rate, versus 74% and 90% respectively for CRFs without a threshold model, short-sign detector, subsign reasoning, and hand appearance-based sign verification.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.1034-1037
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• 2009

Sign language spotting is the task of detecting the start and end points of signs from continuous data and recognizing the detected signs in the predefined vocabulary. The difficulty with sign language spotting is that instances of signs vary in both motion and shape. Moreover, signs have variable motion in terms of both trajectory and length. Especially, variable sign lengths result in problems with spotting signs in a video sequence, because short signs involve less information and fewer changes than long signs. In this paper, we propose a method for spotting variable lengths signs based on semi-CRF (semi-Markov Conditional Random Field). We performed experiments with ASL (American Sign Language) and KSL (Korean Sign Language) dataset of continuous sign sentences to demonstrate the efficiency of the proposed method. Experimental results show that the proposed method outperforms both HMM and CRF.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.768-775
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• 2005

For sign languages are main communication means among hearing-impaired people, there are communication difficulties between speaking-oriented people and sign-language-oriented people. Automated sign-language recognition may resolve these communication problems. In sign languages, finger spelling is used to spell names and words that are not listed in the dictionary. There have been research activities for gesture and posture recognition using glove-based devices. However, these devices are often expensive, cumbersome, and inadequate for recognizing elaborate finger spelling. Use of colored patches or gloves also cause uneasiness. In this paper, a vision-based finger spelling recognition system is introduced. In our method, captured hand region images were separated from the background using a skin detection algorithm assuming that there are no skin-colored objects in the background. Then, hand postures were recognized using a two-dimensional grid analysis method. Our recognition system is not sensitive to the size or the rotation of the input posture images. By optimizing the weights of the posture features using a genetic algorithm, our system achieved high accuracy that matches other systems using devices or colored gloves. We applied our posture recognition system for detecting Korean Sign Language, achieving better than $93\%$ accuracy.

• The Korean Journal of Community Living Science
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• v.23 no.1
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• pp.41-50
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• 2012

This study was performed to understand the depression of children with hearing impairment with relation to their mothers' nurturing attitude and sign language level. The subjects were 131 hearing impaired children aged from 9 to 16 years and their mothers, who had no hearing impairments. The children's depression was assessed by CDI(Kovacs 1983) adapted by Cho and Lee(1990), and the maternal attitude was measured through the instrument developed by Oh and Lee(1982) and revised by Lim(1987). The results were as follows. First, the girls' depression was higher than the boys', and children in a dormitory type of school showed higher depression than those in a general type of school. Second, children's depression did not show differences according to mother-child communication methods but differed according to mothers' sign language level. Children whose mothers had high level of sign language showed the highest depression and those whose mothers had beginning level of sign language showed the lowest depression. And mothers' affective, goal- achieving and rational attitude were negatively related with children's depression. Third, the depression of hearing impairment children was influenced mainly by the maternal affective attitude, and the next order was the type of school the children attend.