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변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
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지인영,김희동 국제언어인문학회 2018 인문언어 Vol.20 No.1
In this study, we discuss the basic technology of Text Summarization based on the deep neural network for natural language processing(NLP). The text summarization task is divided into an extractive summary and an abstractive summary. The extractive summary is a method of extracting a summary of the words used in the input document in the output text, and the abstractive summary is a problem of understanding the input statement and generating a sentence of the same content. The abstractive sentence generation system is based on the encoder-decoder model with attention mechanism, and a selector that can select input sentence is added. The Copy network and Pointer network are the special mechanisms for selector. Such selector systems can make text summarization to be the hybrid form of abstractive and extractive summary. In the future, we expect that accuracy of text summarization will be improved by adding reinforcement learning method.
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지인영,김희동 국제언어인문학회 2017 인문언어 Vol.19 No.2
In this study, we discuss the basic technology of machine learning of the deep neural network for natural language processing(NLP). We explain the distributed vector representation of words. Distributed vector representation is proved to be able to carry semantic meanings and are useful in various NLP tasks. The recurrent neural network(RNN) is employed to get the vector representation of sentences. We discuss the RNN encoder-decoder model and some modifications of the RNN structure to improve the accuracy of the machine translations. To test and verify the accuracy of Google translator, we performed the translation among Korean, English, and Japanese, and examined the meaning change between the original and the translated sentence. In neural network translation, we showed some inaccuracies of the translation such as wrong relation between subject and object, or some omission or repetition of the original meaning. In order to increase the performance and accuracy of machine translation, it is necessary to acquire more data for training.
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지인영 한국체육대학교 1998 敎養敎育硏究所 論文集 Vol.- No.3
The purpose of this paper is to analyse "Aspect" of English utterance, different ways of viewing the internal temporal constituecy of a situation, and to suggest its formal representation in the framework of Situation Semantics. For this purpose, aspectual classes of English utterance are characterized in terms of their own temporal structure of events they describe. Especially, lexicalized aspectual verbs describing onset, middle or end of event, such as start, continue, stop, finish and their logical properties are analysed. Moreover, these aspectual verbs have presuppositions on the temporal meaning of events described, which affects on the interpretation of the following utterance in the context. In this paper, the different temporal presuppositions of aspectual verbs and temporal relations of described events are discussed and analyzed. Fro its formalization it is suggested that the analyzed output can be incorporated into situation semantic representation as resource situation ?? and discourse situation ?? to form a constellation of situations. It is expected that thereby we can get one step further toward a dynamic interpretation of natural language reflecting our empirical world.
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지인영,김희동 한국외국어대학교 통번역연구소 2020 통번역학연구 Vol.24 No.3
There was a big technical progress in the research field of machine translation: the main approach has switched from statistical machine translation (SMT) to neural machine translation (NMT), leading to dramatic improvements in translation quality. Recently, another progress has been taking place from recurrent neural network(RNN)-based NMT to transformer-based NMT (T-NMT). As the performance of NMT has evolved, a lot of research papers for machine translation have been published in the field of interpretation and translation. Their main focus is on whether machine translation can replace human translation, and analyzing the quality of translation results. In this paper, we briefly explain the history of the machine translation research and review the mechanism of NMT. NMT is basically composed of three parts: encoder, attention mechanism, and decoder. Further we discuss the new transformer structure based on the encoder-decoder model. We also discuss the challenges in NMT and explain the research direction or solutions to the problems. Particular attention is given to the mistranslation of NMT, quality of the translation, and robustness against the noises in the training dataset as well as in the testing sentences. In order to test the performance of transformer-based NMT, we used the Google NMT (GNMT) service for 4 languages – Korean, English, German, and Japanese. We confirmed the robustness against sentences with noises. However, we found unexpected volatility of NMT models where the input sentence is semantically and syntactically correct, resulting in critical degradation of translation quality.
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지인영 한국체육대학교 1999 敎養敎育硏究所 論文集 Vol.- No.4
This paper aims to identify the correlation between language and culture or thought and to examine the differences of the Korean and English or American cultures of life, reflected in their proverbs. Especially the dietary lives in both cultures are focused on. First, two leading hypotheses about the relation between language and culture, that is, Linguistic Universal Hypothesis and Linguistic Relativity Hypothesis, are discussed. In the discussion, it is suggested that the relation between the two hypotheses is to be recognized not as exclusive, but as complementary one, because neither of them can provide an adequate and sufficient explanation alone. The examination of the related topic, the color terms, verifies the suggested idea that the Linguistic Relativity Hypothesis is to be considered on the ground of Linguistic Universal Hypothesis. Second, both Korean and English-American cultures of life, represented and implied in their proverbs, are compared and analysed. In the process, the similarities and differences of their dietary cultures are discussed. This analysis also provides strong evidences not only for the close correlation and interaction between language and culture, or thought, but also for a universal cognitive ability every human possesses.
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