• Journal of Korea Multimedia Society
• /
• v.8 no.6
• /
• pp.790-797
• /
• 2005

It is well-known that there are many similarities between Japanese and Korean language. For example, the order of words and the nature of the grammatical conjugation of both languages are almost the same. Another similarity is the frequent omission of the subject from a sentence. Moreover, both languages have honorific expressions and the identical concept for expressing nouns in terms of Chinese characters. Using these similarities, we have developed a word-to-word translation system which does away with any deep level analysis of syntactic and semantic structures of the two languages. If we use these similarities, the direct translation method is superior to the internal language translation method or transfer-based translation method. Although the MT system based on the direct translation method is more easily developed than the ones based on other methods, it may have a lot of difficulties when it tries to select the appropriate target word from ambiguous source verbs. In this paper, we propose a new algorithm to extract the meaning of substantives and to make use of the order of the extracted meaning. We could select $86.5\%$ appropriate verbs in the sample sentences from IPAL-verb-dictionary. $13.5\%$ indicates the cases in which we could not distinguish the meaning of substantives. We are convinced, however, that the succeeding rate can be increased by getting rid of the meaning of verbs thatare not used so often.

• Korean Journal of Cognitive Science
• /
• v.15 no.2
• /
• pp.33-42
• /
• 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)Study of the Eastern Classic
• /
• no.73
• /
• pp.445-473
• /
• 2018

This article deals with the reason for translating Korean Chinese written classics and the image of the person performing the translation. The scope of the research was restricted to South Korea and the translation value of translating the Korean classical texts from the 1960s to the 2018. In the 1960s and 1970s, the discourse of national culture and the Classical Sinology(漢學) discourse centered around the Minjokmunwhachujinhwe(民族文化推進會, National Culture Promotion Association). The discourse of the national culture was paired with the modernization, and the discourse of Classical Sinology(漢學) discourse was a certain antagonism to the discourse of modernization. The translator stereotype in this periods was close to a Classical Sinology(漢學) who could wright Korean letters. The discourse of the national culture led to the establishment of The Academy of Korean Studies by pairing with the discourse of the spiritual culture, and then changed into Korean study discourse in the 1980s. Since the mid 80s, the theory of translation has been introduced byo Kim Yong-ok. The translation of the Chosun dynasty annals, which started in the 70s, made the classical translation discourse in the classical translation field into the national project efficiency discourse. To the Early achievement of state-led gigantic project through group translation, they emphasized coherence and efficiency. On the contrary, the individuality of the translators and aspects of in-depth research have weakened. This discourse also influenced until the early 2000s. These large translation projects were produced by professional translator group. With the establishment of the Institute for the Translation of Korean Classics(Hankuk Kojon Bunyukwon) in 2007, he foundation for the stability of the classical translation business was established, and the classical translation discourse was shifted to the academic discourse centered on classical translation sudies. This discussion was expanded to the request of the establishment of an academic institution called the Classical Translation Graduate School, with a discussion on the academic identities of classical translation studies. The imagies of translators, paired with the academic discourse of this period, and that the classical translators must be classical scholars and translators, are begun to be requested. Thus, the classical translation value discourse changed with the passage of time, and the imagies of classical translators have been changed accordingly.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.51 no.10
• /
• pp.446-452
• /
• 2002

For most of pattern recognition applications, it is required to correctly recognize patterns even if they have translation variations. In this paper, to achieve the goal of translation invariant pattern recognition, we propose a new generalized translation invariant second-order neural network using a constraint on the weights. The weight constraint is implemented using generalized translation invariant features which are accumulated sums of pixel combinations. Simulation results will be given to demonstrate that the proposed second-order neural network has the generalized translation invariant property.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.5
• /
• pp.265-270
• /
• 2022

San Mao is a prominent Taiwanese female writer. She created many works in a unique style based on what she experienced and studied through her experience of studying abroad. Among them, 『Daocaoren Shouj i』 is a prose that records episodes of overseas life. There are two Korean translations of this work. Different translators used different translation strategies. TT1 used a lot of semantic translation to emphasize and translate a lot of exotic feelings. On the other hand, TT2 pursued natural translation by using a communicative translation strategy. In addition, the peculiarity is that both translations attempted 'creative translation' and intentionally 'transformed' and translated. This creative translation helps the reader to immerse and understand the work. With this study as an opportunity, we hope that various follow-up studies on San Mao's translation will be conducted.

• Korean Journal of Computational Design and Engineering
• /
• v.1 no.2
• /
• pp.87-96
• /
• 1996

IGES is a file format which has gained widespread use but has certain limitations such as limited information coverage and ambiguous definitions. In order to overcome the limitations of existing neutral file formats, STEP has been developed as a more comprehensive mechanism for product data exchange by ISO. This paper describes a file translation system between IGES and STEP. In this system, three EXPRESS schemata are defined for IGES, STEP and the translation relationship between IGES and STEP. Object codes are generated from the schemata and linked with file access libraries to IGES and STEP files. The translation was verified by visualization and reverse translation. The system developed in this study can easily applied to translate other file formats because the file structure and translation relationship are defined in EXPRESS - a high level information modeling language.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.1
• /
• pp.124-129
• /
• 2006

This parer presents a method of ranking translation word selection for Korean verbs based on lexical knowledge contained in a bilingual Korean-English dictionary and WordNet that are easily obtainable knowledge resources. We focus on deciding which translation of the target word is the most appropriate using the measure of semantic relatedness through the 45 extended relations between possible translations of target word and some indicative clue words that play a role of predicate-arguments in source language text. In order to reduce the weight of application of possibly unwanted senses, we rank the possible word senses for each translation word by measuring semantic similarity between the translation word and its near synonyms. We report an average accuracy of $51\%$ with ten Korean ambiguous verbs. The evaluation suggests that our approach outperforms the default baseline performance and previous works.

• Communications for Statistical Applications and Methods
• /
• v.27 no.3
• /
• pp.313-326
• /
• 2020

Deep Learning is the most important key to the development of Artificial Intelligence (AI). There are several distinguishable architectures of neural networks such as MLP, CNN, and RNN. Among them, we try to understand one of the main architectures called Recurrent Neural Network (RNN) that differs from other networks in handling sequential data, including time series and texts. As one of the main tasks recently in Natural Language Processing (NLP), we consider Neural Machine Translation (NMT) using RNNs. We also summarize fundamental structures of the recurrent networks, and some topics of representing natural words to reasonable numeric vectors. We organize topics to understand estimation procedures from representing input source sequences to predict target translated sequences. In addition, we apply multiple translation models with Gated Recurrent Unites (GRUs) in Keras on English-Korean sentences that contain about 26,000 pairwise sequences in total from two different corpora, colloquialism and news. We verified some crucial factors that influence the quality of training. We found that loss decreases with more recurrent dimensions and using bidirectional RNN in the encoder when dealing with short sequences. We also computed BLEU scores which are the main measures of the translation performance, and compared them with the score from Google Translate using the same test sentences. We sum up some difficulties when training a proper translation model as well as dealing with Korean language. The use of Keras in Python for overall tasks from processing raw texts to evaluating the translation model also allows us to include some useful functions and vocabulary libraries as well.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.2
• /
• pp.185-192
• /
• 2019

In the case of a hearing impaired person using sign language, there are many difficulties in communicating with a normal person who does not understand sign language. The sign language translation system is a system that enables communication between the hearing impaired person using sign language and the normal person who does not understand sign language in this situation. Previous studies on sign language translation systems for communication between normal people and hearing impaired people using sign language are classified into two types using video image system and shape input device. However, the existing sign language translation system does not solve such difficulties due to some problems. Existing sign language translation systems have some problems that they do not recognize various sign language expressions of sign language users and require special devices. Therefore, in this paper, a sign language translation system using an artificial neural network is devised to overcome the problems of the existing system.

• Journal of Digital Contents Society
• /
• v.19 no.1
• /
• pp.75-83
• /
• 2018

Multicultural family members have difficulty in educating their children due to language differences. In order to solve these difficulties, it is necessary to provide smart translation services that enable them easily and quickly access real-life vocabularies. However, the current automatic translation technology is being developed in dominant languages such as English, Chinese, and Japanese. There are also limitations to translating special-purpose terms such as documents of schools and instructions of public institutions. In this study, we propose a real-time automatic word translation service for multicultural family members who understand beginner level Korean. The service automatically analyzes the semantics of each word in the Korean sentences and provides a word-by-word translation. This study includes semantic analysis research for Korean language, building multilingual translation knowledge, and fusion study of language education. We evaluated the word translation service for migrant women from Vietnam and Japan and obtained meaningful evaluation results.