• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.993-997
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• 2009

Clustering is well known method and that can be used in statistical machine translation. In this paper we propose a corpus clustering method using syntactic structure and POS information of dependency grammar. And using this cluster language model as additional feature to phrased-based statistical machine translation system to improve translation Quality.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.799-809
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• 2000

In this paper we propose a nonparametric one sided test for location parameters in p-variate(p$\geq$2) location translation model. The exact null distributions of test statistics are calculated by permutation principle in the case of relatively small sample sizes and the asymptotic distributions are also considered. The powers of various tests are compared through computer simulation and thep-values with real data are also suggested through example.

• Journal of Korean Medical classics
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• v.24 no.1
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• pp.57-71
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• 2011

Although there have been many endeavors aimed at the standardization and globalization of Korean medicine over a long period of time, the access to information on Oriental medical classics has been relatively poor due to the lack of appropriate translation methodology and standard terminology. In order to overcome existing barriers, continuous effort towards precise translation adopting a standard terminology should be maintained. As a part of this procedure, we planned to publish a part of "Classic of difficult issues(難經)" in three sections, and the first two studies have already been published. Based on the methodology and approaches of previous studies, this third study aims to translate parts of "Classic of difficult issues(難經)" into English, beginning with "The Sixteenth Question", and adopting "WHO-IST" terminology. The outcomes of this study are presented as follows: First, based on the result of existing translation studies and the outcome of "WHO-IST", English translation of "Classic of difficult issues(難經)" from "the Sixteenth Question" to "The Twenty-second Question" is offered, hoping to set a model of translation study which can be communicated universally. Second, in order to pave the way for future success in establishing translation studies, it is natural to verify the effectiveness and practicality of standard terminologies including the outcome of "WHO-IST". Continuous translation studies will be required in order to obtain constant feedback and adopt more suitable guidelines during the standardization process. Taking this into consideration, further translation studies of Oriental medical classics including "Classic of difficult issues(難經)" should be continued.

• Korean Journal of Health Education and Promotion
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• v.2 no.1
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• pp.1-19
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• 2000

With rapid economic development, the emphasis of the public health movement in Korea has shifted towards addressing the burden of chronic disease. With this shift in direction comes a greater focus on health behaviour and the need for planning models to assist in lifestyle modification programs. The Health Belief Model (HBM), which originated in the US, has generated more research than any other theoretical approach to describe and predict the health behaviour of individuals. In recent years it has been applied in many different cultures and modifications have been suggested to accommodate different cultures. Given the centrality of language and culture, any attempts to use models of health behaviour developed in a different culture, must be studied and tested for local applicability. The paper reviews the applicability and suitability of the HBM in Korea, in the context of the Korean language and culture. The HBM has been used in Korea for almost three decades. The predictability of the HBM has varied in Korean studies as in other cultures. Overall, this literature review indicates that the HBM has been found applicable in predicting health and illness behaviours by Korean people. However if the HBM is used in a Korean context, the acquisition of health knowledge is an important consideration. Most new knowledge in the health sciences is originally published in English and less frequently in another foreign language. Most health knowledge in Korea is acquired through the media or from health professionals and its acquisition often involves translation from the original. The selection of articles for translation and the accuracy of translation into language acceptable in the Korean culture become important determinants of health knowledge. As such translation becomes an important part of the context of the HBM. In this paper modifications to the HBM are suggested to accommodate the issues of language and knowledge in Korea.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.1-7
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• 2021

In the latest trend of machine translation research, the model is pretrained through a large mono lingual corpus and then finetuned with a parallel corpus. Although many studies tend to increase the amount of data used in the pretraining stage, it is hard to say that the amount of data must be increased to improve machine translation performance. In this study, through an experiment based on the mBART model using parallel corpus filtering, we propose that high quality data can yield better machine translation performance, even utilizing smaller amount of data. We propose that it is important to consider the quality of data rather than the amount of data, and it can be used as a guideline for building a training corpus.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.199-208
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• 2021

Automatic Post Editing(APE) is the study that automatically correcting errors included in the machine translated sentences. The goal of APE task is to generate error correcting models that improve translation quality, regardless of the translation system. For training these models, source sentence, machine translation, and post edit, which is manually edited by human translator, are utilized. Especially in the recent APE research, multilingual pretrained language models are being adopted, prior to the training by APE data. This study deals with multilingual pretrained language models adopted to the latest APE researches, and the specific application method for each APE study. Furthermore, based on the current research trend, we propose future research directions utilizing translation model or mBART model.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.21-27
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• 2003

In these paper, we define object models in order to represent a correct analysis model, propose translation method to formal specification necessary to uniform and standard. The translated model provide to correctness, consistency and completeness. If it is happen to error in the VDM specification, we can verify model to adapt initial object model step. It increase correctness to retrieval, reduce the costs and efforts of after development because of the verified model used to basic specification in design step.

• Asia Marketing Journal
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• v.12 no.4
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• pp.1-25
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• 2011

Brand names are often considered as a part of product and important extrinsic cues of product evaluation, when consumers make purchasing decisions. For a company, brand names are also important assets. Building a strong brand name in the Chinese commonwealth is a main challenge for many global companies. One of the first problem global company has to face is how to translate English brand name into Chinese brand name. It is very difficult decision because of cultural and linguistic differences. Western languages are based on an alphabet phonetic system, whereas Chinese are based on ideogram. Chinese speakers are more likely to recall stimuli presented as brand names in visual rather than spoken recall, whereas English speakers are more likely to recall the names in spoken rather than in visual recall. We interpret these findings in terms of the fact that mental representations of verbal information in Chinese are coded primarily in a visual manner, whereas verbal information in English is coded by primarily in a phonological manner. A key linguistic differences that would affect the decision to standardize or localize when transferring English brand name to Chinese brand name is the writing system. Prior Chinese brand naming research suggests that popular Chinese naming translations foreign companies adopt are phonetic, semantic, and phonosemantic translation. The phonetic translation refers to the speech sound that is produced, such as the pronunciation of the brand name. The semantic translation involves the actual meaning of and association made with the brand name. The phonosemantic translation preserves the sound of the brand name and brand meaning. Prior brand naming research has dealt with word-level analysis in examining English brand name that are desirable for improving memorability. We predict Chinese brand name suggestiveness with different translation methods lead to different levels of consumers' evaluations. This research investigates the structural linguistic characteristics of the Chinese language and its impact on the brand name evaluation. Otherwise purpose of this study is to examine the effect of brand concept on the evaluation of brand name. We also want to examine whether the evaluation is moderated by Chinese translation types. 178 Taiwanese participants were recruited for the research. The following findings are from the empirical analysis on the hypotheses established in this study. In the functional brand concept, participants in Chinese translation by semantic were likely to evaluate positively than Chinese translation by phonetic. On the contrary, in the symbolic brand concept condition, participants in Chinese translation by phonetic evaluated positively than by semantic. And then, we found Chinese translation by phonosemantic was most favorable evaluations regardless of brand concept. The implications of these findings are discussed for Chinese commonwealth marketers with respect to brand name strategies. The proposed model helps companies to effectively select brand name, making it highly applicable for academia and practitioner. name and brand meaning. Prior brand naming research has dealt with word-level analysis in examining English brand name that are desirable for improving memorability. We predict Chinese brand name suggestiveness with different translation methods lead to different levels of consumers' evaluations. This research investigates the structural linguistic characteristics of the Chinese language and its impact on the brand name evaluation. Otherwise purpose of this study is to examine the effect of brand concept on the evaluation of brand name. We also want to examine whether the evaluation is moderated by Chinese translation types. 178 Taiwanese participants were recruited for the research. The following findings are from the empirical analysis on the hypotheses established in this study. In the functional brand concept, participants in Chinese translation by semantic were likely to evaluate positively than Chinese translation by phonetic. On the contrary, in the symbolic brand concept condition, participants in Chinese translation by phonetic evaluated positively than by semantic. And then, we found Chinese translation by phonosemantic was most favorable evaluations regardless of brand concept. The implications of these findings are discussed for Chinese commonwealth marketers with respect to brand name strategies. The proposed model helps companies to effectively select brand name, making it highly applicable for academia and practitioner.

• Journal of Intelligence and Information Systems
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• v.15 no.3
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• pp.53-65
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• 2009

The part-of-speech determination is necessary for resolving the part-of-speech ambiguity in English-Korean machine translation. The part-of-speech ambiguity causes high parsing complexity and makes the accurate translation difficult. In order to solve the problem, the resolution of the part-of-speech ambiguity must be performed after the lexical analysis and before the parsing. This paper proposes the CatAmRes model, which resolves the part-of-speech ambiguity, and compares the performance with that of other part-of-speech tagging methods. CatAmRes model determines the part-of-speech using the probability distribution from Bayesian network training and the statistical information, which are based on the Penn Treebank corpus. The proposed CatAmRes model consists of Calculator and POSDeterminer. Calculator calculates the degree of appropriateness of the partof-speech, and POSDeterminer determines the part-of-speech of the word based on the calculated values. In the experiment, we measure the performance using sentences from WSJ, Brown, IBM corpus.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.37-44
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• 2021

Quality estimation (QE) can evaluate the quality of machine translation output even for those who do not know the target language, and its high utilization highlights the need for QE. QE shared task is held every year at Conference on Machine Translation (WMT), and recently, researches applying Pretrained Language Model (PLM) are mainly being conducted. In this paper, we conduct a survey on the QE task and research trends, and we summarize the features of PLM. In addition, we used a multilingual BART model that has not yet been utilized and performed comparative analysis with the existing studies such as XLM, multilingual BERT, and XLM-RoBERTa. As a result of the experiment, we confirmed which PLM was most effective when applied to QE, and saw the possibility of applying the multilingual BART model to the QE task.