• International Journal of Advanced Culture Technology
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• 제6권2호
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• pp.65-71
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• 2018

In the digital era, news consumption is not confined in geological boundaries. Technological advances bring the instant dissemination of news into life and allow news audience to consume events that occur far away almost in real time. The transmission has blurred the boundary between traditional media and new media, and the one between physical and virtual world. That is, what if a journalist applies news framing to the news translation process? This paper aims to investigate the gap between the ST and the TT created when the source news texts undergo a translation process. To achieve this aim, the appraisal theory developed by White (2003) is employed to identify a difference between the ST and the TT. Furthermore, we have attempted to identify differences between soft news stories and hard news stories while the STs from both news stories are translated into the TTs. Two time-sensitive events, Hugh Grant's marriage and a U.S. and North Korea summit, were selected. The former (a soft news story) is extracted from the Telegraph and the latter (a hard news story) is from the Washington post. As a result, it was found that such strategies as attitude, engagement, and judgment were used when the source news texts from the hard news story are translated into the target news texts. Under the appraisal theory, the strategies involve evaluative language which refers to positive or negative language that judges the worth of entities. In general, it is said that a journalist frames the SS (especially from the hard news story) to convey his ideology to news consumers. Hypothetically, we assume that a similar framing process takes place in deriving the TT from the SS of the hard news story. Thus, we could conclude that the TT from the hard news story differs from the TT from the soft news story and that the difference can be explained within the framework of White's appraisal theory.

• International Journal of Advanced Culture Technology
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• 제12권2호
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• pp.161-166
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• 2024

As globalization has accelerated, the use of English loanwords is increasing in South Korea. In this paper, we have analyzed news stories from four Korean quality newspapers-Chosun Ilbo, Dong-A Ilbo, KyungHyang Sinmun, and Chung-Ang Ilbo to investigate the usage of English loanwords in news texts. Thirty-eight news stories on life, politics, business and IT were collected from the four newspapers and then analyzed based on the five types of loanwords-Direct, Mixed Code Combination, Clipping and Neologism and Double Notation, partly following Lee's and Rudiger's classification. As a result, the followings were revealed: first, the use of the category Direct was overwhelming the others with 90%, indicating that English loanwords were not translated from its source language and introduced into Korean directly with little modification; second, the use of English loanwords was significantly higher in the sections of business and IT than in other sectors, implying that English loanwords function in a similar way as a lingua franca does within those fields. Furthermore, the linguistic trends can provide a basic guide for translators to make an informed decision between the use of English loanwords and its translated Korean version in English-into Korean translation.

• International Journal of Internet, Broadcasting and Communication
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• 제12권2호
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• pp.127-136
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• 2020

This paper presents an environment for rule-based English-Korean machine translation system, which supports the translation domain adaptation and the continuous translation quality improvement. For the purposes, corpus is essential, from which necessary information for translation will be acquired. The environment consists of a corpus construction part and a translation knowledge extraction part. The corpus construction part crawls news articles from some newspaper sites. The extraction part builds the translation knowledge such as newly-created words, compound words, collocation information, distributional word representations, and so on. For the translation domain adaption, the corpus for the domain should be built and the translation knowledge should be constructed from the corpus. For the continuous improvement, corpus needs to be continuously expanded and the translation knowledge should be enhanced from the expanded corpus. The proposed web-based environment is expected to facilitate the tasks of domain adaptation and translation system improvement.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.313-326
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• 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.

• 한국인지과학회:학술대회논문집
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• 한국인지과학회 2000년도 한글 및 한국어 정보처리
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• pp.350-357
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• 2000

본 논문은 근 몇 년간 꾸준히 진행되어진 중한 기계번역시스템에 대한 연구의 기초 위에서, 뉴스 타이틀 번역이라는 특정 도메인에 초점을 맞추어 언어적 특성을 살펴보고, 중한 언어적 유사성에 기반 한 뉴스 타이틀 번역을 위한 중한 기계번역시스템에 대하여 설명한다.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2007년도 정기학술대회
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• pp.489-497
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• 2007

Named entity translation plays an important role in many applications, such as information retrieval and machine translation. In this paper, we focus on translating person names, the most common type of name entity in Korean-Chinese cross language information retrieval (KCIR). Unlike other languages, Chinese uses characters (ideographs), which makes person name translation difficult because one syllable may map to several Chinese characters. We propose an effective hybrid person name translation method to improve the performance of KCIR. First, we use Wikipedia as a translation tool based on the inter-language links between the Korean edition and the Chinese or English editions. Second, we adopt the Naver people search engine to find the query name's Chinese or English translation. Third, we extract Korean-English transliteration pairs from Google snippets, and then search for the English-Chinese transliteration in the database of Taiwan's Central News Agency or in Google. The performance of KCIR using our method is over five times better than that of a dictionary-based system. The mean average precision is 0.3490 and the average recall is 0.7534. The method can deal with Chinese, Japanese, Korean, as well as non-CJK person name translation from Korean to Chinese. Hence, it substantially improves the performance of KCIR.

• International Journal of Advanced Culture Technology
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• 제10권3호
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• pp.104-110
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• 2022

This paper aims to analyze discourse metaphors by paying attention to Seoul mayoral by-election, mainly focusing on election campaign and its related news articles. The 2021 Seoul mayoral by-election was held because the former mayor died in an apparent suicide after he was accused of years of sexual harassment to a former secretary. But in the run-up to the by-election, the newly coined word 'alleged victim' from the ruling party caused a big controversy because the party attempted to deny the authenticity of the secretary's claim by calling her "an alleged victim," instead of "a victim" to defend the former mayor who is a member of the ruling party, implying that the woman's claim is just an allegation with no proof. Thus, this paper has analyzed how news stories were reported with regard to the word 'alleged victim' poser on news stories in two Korean quality newspapers, a conservative newspaper (Chosun Ilbo) and a liberal newspaper (Hankyoreh) from March 1 to April 1, 2021 and analyzed them with the framework of Lakoff and Johnson's Conceptual Metaphor Theory(1980). The findings are as follows: (i) the conservative newspaper reports this issue much more than the liberal newspaper; (ii) both quality newspapers follow the metaphor principles by Conceptual Metaphor Theory; (iii) the conservative newspaper is more likely to follow the Strick Father model (a conservative model) while the liberal newspaper is to follow the Nurturant Parent model (a liberal model), thus indicating that each newspaper's ideology is well represented by the models of Conceptual Metaphor Theory

• 디지털콘텐츠학회 논문지
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• 제18권5호
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• pp.949-956
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• 2017

오늘날 인터넷 신문들은 대중적인 디지털 콘텐츠로 자리잡고 있다. 인터넷 신문의 시각적 인터페이스는 대동소이하나 그 골조를 이루는 HTML의 수준 및 규격은 천차만별이다. HTML의 가장 기본적인 목적이 다른 컴퓨터도 이해할 수 있도록 문서를 의미론적으로 기술하는 것이기에 HTML5에서 문서의 시맨틱스(semantics)는 더욱 강조되고 있다. 본 연구에서는 글로벌 인터넷 신문 8개의 HTML을 대조군으로 삼아 한국의 110개 인터넷 신문을 분석하여 실질적으로 문서에 사용된 HTML 규격을 점검하고 그 시맨틱스의 수준을 진단하였다. 분석 결과 조사대상인 110개 한국의 인터넷신문 중 68%가 HTML4 규격에 해당하는 것으로 나타났으며, 110개 중 9%에 해당하는 10개의 웹사이트만이 대조군으로 조사한 글로벌 인터넷신문과 동일한 수준의 HTML5 규격으로 작성되었으며 적극적인 시맨틱스를 적용하고 있는 것으로 나타났다. 번역기술이 인공지능으로 인해 한층 개선되고 있는 이 시점에 한국 인터넷신문의 디지털 콘텐츠들이 세계와 소통하기 위해서는 더욱 더 적극적인 시맨틱스를 적용한 HTML 문서 작성 플랫폼으로의 규격 전환이 필요하다.

• International Journal of Advanced Culture Technology
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• 제8권4호
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• pp.207-211
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• 2020

In the global economy, trade is not confined in geological boundaries, enhancing the international relation among countries. However, the trade tension between the largest economy and the second-largest economy raise concerns among the world economies, enhancing the uncertainties around world. In particular, the trade tension between the two countries is highly related with South Korea's trade balance, because the country is highly dependent on the trade with the two countries. Given this, we analyzed the news editorials published in Korean quality newsaper, with related to U.S. and China Trade War by looking at the ideological perspectives of news outlets or journalists to the issue within the framework of critical discourse analysis. In particular we gave a special attention to the attitude to each country in order to investigate their ideological stance to the country, following van Dijk (1998)' ideological square. The results are as follows: first, the Chosun Ilbo emphasized 'their' bad properties directly and aggresively, while the Hankyoreh designated the U.S. as a member of an out-group, thus mitigating 'our' bad quatilies; Second, the two strategies of emphasis and mitigation enabled both newspapers to reinforce in-group homogeneity and out-group exclusion. Thus, we could conclude that the editorial is a clear indicator to show the news outlet's ideological stance to each country in regard to the trade issue.

• 대한음성학회지:말소리
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• 제68권
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• pp.95-114
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• 2008

The recent growing popularity of statistical methods in machine translation requires much more large parallel corpora. A Korean-English parallel corpus, however, is not yet enoughly available, little research on this subject is being conducted. In this paper we present a hybrid method of aligning sentences for Korean-English parallel corpora. We use bilingual news wire web pages, reading comprehension materials for English learners, computer-related technical documents and help files of localized software for building a Korean-English parallel corpus. Our hybrid method combines sentence-length based and word-correspondence based methods. We show the results of experimentation and evaluate them. Alignment results from using a full translation model are very encouraging, especially when we apply alignment results to an SMT system: 0.66% for BLEU score and 9.94% for NIST score improvement compared to the previous method.