• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.998-1008
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• 2004

There are many syntactic similarities between Japanese and Korean languages. Using these similarities, we can make out the Japanese-Korean translation system without most of syntactic analysis and semantic analysis. To improve the translation rates greatly, we have been developing the Japanese-Korean translation system using these similarities from several years ago. However, the system remains some problems such as a translation of inflected words, processing of multi-translatable words and so on. In this paper, we suggest the new method of Japanese-Korean translation by using relations of two neighboring words. To solve the problems, we investigated the connection rules of auxiliary verbs priority. And we design the translation table which is consists of entry tables and connection forms tables. A case of only one translation word, we can translate a Korean to Japanese by direct matching method use of only entry table, otherwise we have to evaluate the connection value by connection forms tables and then we can select the best translation word.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.1-13
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• 2004

This paper presents a method for the multilingual product retrieval agent through XML and the semantic networks in e-commerce. Retrieval for products is an important process, since it represents interfaces of the customer contact to the e-commerce. Keyword-based retrieval is efficient as long as the product information is structured and organized. But when the product information is expressed across many online shopping malls, especially when it is expressed in different languages with cultural backgrounds, buyers' product retrieval needs language translation with ambiguities resolved in a specific context. This paper presents a RDF modeling case that resolves semantic problems in the representation of product information and across the boundaries of language domains. With adoption of UNSPSC code system, this paper designs and implements an architecture for the multilingual product retrieval agents. The architecture is based on the central repository model of product catalog management with distributed updating processes. It also includes the perspectives of buyers and suppliers. And the consistency and version management of product information are controlled by UNSPSC code system. The multilingual product names are resolved by semantic networks, thesaurus and ontology dictionary for product names.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1535-1545
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• 2022

Sign language has completely different meaning depending on the direction of the hand or the change of facial expression even with the same gesture. In this respect, it is crucial to capture the spatial-temporal structure information of each movement. However, sign language translation studies based on Sign2Gloss2Text only convey comprehensive spatial-temporal information about the entire sign language movement. Consequently, detailed information (facial expression, gestures, and etc.) of each movement that is important for sign language translation is not emphasized. Accordingly, in this paper, we propose Spatial-temporal Keypoints Centered Sign2Gloss2Text Translation, named STKC-Sign2 Gloss2Text, to supplement the sequential and semantic information of keypoints which are the core of recognizing and translating sign language. STKC-Sign2Gloss2Text consists of two steps, Spatial Keypoints Embedding, which extracts 121 major keypoints from each image, and Temporal Keypoints Embedding, which emphasizes sequential information using Bi-GRU for extracted keypoints of sign language. The proposed model outperformed all Bilingual Evaluation Understudy(BLEU) scores in Development(DEV) and Testing(TEST) than Sign2Gloss2Text as the baseline, and in particular, it proved the effectiveness of the proposed methodology by achieving 23.19, an improvement of 1.87 based on TEST BLEU-4.

• Annual Conference on Human and Language Technology
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• 2014.10a
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• pp.56-60
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• 2014

기계학습 방법에 기반한 자연어 분석은 학습 데이터가 필요하다. 학습 데이터가 구축된 소스 도메인이 아닌 다른 도메인에 적용할 경우 한국어 의미역 인식 기술은 15% 정도 성능 하락이 발생한다. 본 논문은 이러한 다른 도메인에 적용시 발생하는 성능 하락 현상을 극복하기 위해서 기존의 소스 도메인 학습 데이터를 활용하여, 소규모의 타겟 도메인 학습 데이터 구축만으로도 성능 하락을 최소화하기 위해 한국어 의미역 인식 기술에 prior 모델을 제안하며 기존의 도메인 적응 알고리즘과 비교 실험하였다. 추가적으로 학습 데이터에 사용되는 자질 중에서, 형태소 태그와 구문 태그의 자질 값을 기존보다 단순하게 적용하여 성능의 변화를 실험하였다.

• Korean Journal of Cognitive Science
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• v.15 no.2
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• pp.33-42
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• 2004

There are many syntactic similarities between Japanese and Korean language. These similarities enable us to build Japanese-Korean translation systems without depending cm sophisticated syntactic analysis and semantic analysis. To further improve translation accuracy, we have been developing a Japanese-Korean translation system using these similarities for several years. However, there still remain some problems with regard to translation of inflected words, processing of multi-translatable words and so on. In this paper, we propose a new method for Japanese-Koran machine translation by using the relationships of two neighboring words. To solve the problems, we investigate the connection rules of auxiliary verb priority. And we design the translation table, which consists of entry tables and connection form tables. for unambiguous words, we can translate a Japanese word to the corresponding Korean word in terms of direct-matching method by consulting the only entry table. Otherwise we have to evaluate the connection value computed from connection form tables and then we can select the most appropriate target word.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.749-758
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• 2004

In this paper, we propose a new method utilizing only raw corpus without additional human effort for disambiguation of target word selection in English-Korean machine translation. We use two data-driven techniques; one is the Latent Semantic Analysis(LSA) and the other the Probabilistic Latent Semantic Analysis(PLSA). These two techniques can represent complex semantic structures in given contexts like text passages. We construct linguistic semantic knowledge by using the two techniques and use the knowledge for target word selection in English-Korean machine translation. For target word selection, we utilize a grammatical relationship stored in a dictionary. We use k- nearest neighbor learning algorithm for the resolution of data sparseness Problem in target word selection and estimate the distance between instances based on these models. In experiments, we use TREC data of AP news for construction of latent semantic space and Wail Street Journal corpus for evaluation of target word selection. Through the Latent Semantic Analysis methods, the accuracy of target word selection has improved over 10% and PLSA has showed better accuracy than LSA method. finally we have showed the relatedness between the accuracy and two important factors ; one is dimensionality of latent space and k value of k-NT learning by using correlation calculation.

• Journal of KIISE:Software and Applications
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• v.27 no.3
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• pp.302-313
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• 2000

In English-Korean machine translation, transitive verb-objective collocation is utilized for accurate translation of an English verbal phrase into Korean. This paper presents an algorithm for correct verb translation based on the k-nearest neighbor learning. The semantic distance is defined on the WordNet for the k-nearest neighbor learning. And we also present algorithms for automatic collocation dictionary optimization. The algorithms extract transitive verb-objective pairs as training examples from large corpora and minimize the examples, considering the tradeoff between translation accuracy and example size. Experiments show that these algorithms optimized collocation dictionary keeping about 90% accuracy for a verb 'build'.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.48-54
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• 2000

This Paper classified korean Parts-of-speech for korean-english machine translation and investigated morphological characters of each parts-of-speech. Korean standard grammar classified parts-of-speech by semantic, functional and formal character. Many rules make a difficulties the understanding of grammar structure and parts-of-speech classification and it is necessary to preprocess at machine translation. This paper classified korean parts-of-speech by one rule. The parts-of-speech suggested in this paper have a same syntactic role and same parts-of-speech with english dictionary, and express the structure of korean sentence. And also it can make target language by pattern matching in korean-english translation.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2025-2037
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• 1997

The concept-based translation system, which is a part of the Korean spoken language translation system, translates spoken utterances from Korean speech recognizer into one of English, Japanese and Korean in a travel planning task. Our system regulates semantic rather than the syntactic category in order to process the spontaneous speech which tends to be regarded as the one ungrammatical and subject to recognition errors. Utterances are parsed into concept structures, and the generation module produces the sentence of the specified target language. We have developed a token-separator using base-words and an automobile grammar corrector for Korean processing. We have also developed postprocessors for each target language in order to improve the readability of the generation results.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.259-264
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• 2021

In modern socity, online communication plays a vital role in social interaction of communicities. It is so common for online users to see display advertisements online while surting the Net. Specifically, most web banners diaplayed on portral sites consist of words, phrase, and sentences. Considering that the primary purpose of adversiting is persuation, the advertisement such as web banners is an examplary case to show the interaction among pragmatics, translation and advertising because the linguistic expressions employed in the banners represent its pragmatic use, leading to persuation and functioning as a communicative tool for the smooth communication between source text producers (adversisers) and target audience (online users). This can be part of the so-called translation process. In particular, we can easily witness the use of English words in web banners. Thus, this paper looks at web banners displayed on major four portal sites-Naver, Daum, Nate, and Zum, giving a special attention to the content contained in the web banners as well as the use of English words. As s result, we found that the frequencies of English words in each portal site were higher when the advertised products were targeting young online users, whereas the frequencies were lower when the users are older group than young people. The finding supports the prgramatic perspective that linguistic expressions are understood in social contexts and shows the so-called translation process which involves a shift from semantic meaning of words to their pragmatic use. Finally, we can conclude that the interaction is possible when we have the framework where translation, pragmatics, and advertising are all communitative components for social interaction within social contexts.