• The Journal of the Acoustical Society of Korea
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• v.18 no.4
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• pp.17-22
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• 1999

It is difficult to integrate the speech processing systems and machine translation system in the spoken language translation system by reason that each system uses its own data and basic processing unit. So, we need a common I/O unit which is used in the whole system. In this paper, we propose a Pscudo-Morpheme as the interface between speech processing systems and language translation system. We implement a morphological analysis system for Pseudo-morpheme. The speech processing system using this pseudo-morpheme can get better result than other systems using the phrase or the general morpheme. So, the quality of the whole spoken language translation system can be improved. The analysis-ratio of our implemented system is 98.9%. This is similar to the common morphological analysis systems.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.245-253
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• 2022

Commenced in 1954 by IBM, machine translation has expanded immensely, particularly in this period. Machine translation can be broken into seven main steps namely- token generation, analyzing morphology, lexeme, tagging Part of Speech, chunking, parsing, and disambiguation in words. Morphological analysis plays a major role when translating Indian languages to develop accurate parts of speech taggers and word sense. The paper presents various machine translation methods used by different researchers for Indian languages along with their performance and drawbacks. Further, the paper concentrates on parts of speech (POS) tagging in Marathi dialect using various methods such as rule-based tagging, unigram, bigram, and more. After careful study, it is concluded that for machine translation, parts of speech tagging is a major step. Also, for the Marathi language, the Hidden Markov Model gives the best results for parts of speech tagging with an accuracy of 93% which can be further improved according to the dataset.

• Annual Conference on Human and Language Technology
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• 2019.10a
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• pp.258-261
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• 2019

딥러닝을 이용한 Sequence to Sequence 모델의 등장과 Multi head Attention을 이용한 Transformer의 등장으로 기계번역에 많은 발전이 있었다. Transformer와 같은 성능이 좋은 모델들은 대량의 병렬 코퍼스를 가지고 학습을 진행하였는데 대량의 병렬 코퍼스를 구축하는 것은 시간과 비용이 많이 드는 작업이다. 이러한 단점을 극복하기 위하여 합성 코퍼스를 만드는 기법들이 연구되고 있으며 대표적으로 Back Translation 기법이 존재한다. Back Translation을 이용할 시 단일 언어 데이터를 가상 병렬 데이터로 변환하여 학습데이터의 양을 증가 시킨다. 즉 말뭉치 확장기법의 일종이다. 본 논문은 Back Translation 뿐만 아니라 Copied Translation 방식을 통한 다양한 실험을 통하여 데이터 증강기법이 기계번역 성능에 미치는 영향에 대해서 살펴본다. 실험결과 Back Translation과 Copied Translation과 같은 데이터 증강기법이 기계번역 성능향상에 도움을 줌을 확인 할 수 있었으며 Batch를 구성할 때 상대적 가중치를 두는 것이 성능향상에 도움이 됨을 알 수 있었다.

• Journal of English Language & Literature
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• v.57 no.6
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• pp.1173-1198
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• 2011

In this paper, I discuss Chaucer's Clerk's Tale by viewing the relationship between Walter and Griselda as that of a medieval translator and his translation. My major concern is how a medieval translation can serve power, more specifically the consolidation of power under particular historical circumstances. The motive and the process of Walter's creative translation of Griselda are closely examined to show that his translation, which includes a creation of a new Griselda as a pinnacle of wifely virtue of patience, is performed as a form of political propaganda, ultimately aimed at strengthening his governing power over his people and land. My discussion of the Clerk's Tale ends with the comparison of the two translators, Walter and the Clerk, the latter of whom is an example of an unsuccessful translator for his lack of creation in the translation.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.69-80
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• 2021

Neural machine translation using deep neural network has emerged as a mainstream research, and an abundance of investment and studies on model structure and parallel language pair have been actively undertaken for the best performance. However, most recent neural machine translation studies pass along decoding strategy to future work, and have insufficient a variety of experiments and specific analysis on it for generating language to maximize quality in the decoding process. In machine translation, decoding strategies optimize navigation paths in the process of generating translation sentences and performance improvement is possible without model modifications or data expansion. This paper compares and analyzes the significant effects of the decoding strategy from classical greedy decoding to the latest Dynamic Beam Allocation (DBA) in neural machine translation using a sequence to sequence model.

• Industry Promotion Research
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• v.5 no.1
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• pp.73-87
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• 2020

The purpose of this paper was to find examples of a group of interpretations while biased toward the translation of the manuscripts of Myeongnology, and to apply the criteria of the translation of the manuscripts of Myeongnology in accordance with the criteria of SIN(信), DAL(達), and AH(雅) of EOM-BOK. Since the original author's intention should be faithfully reflected, the translation of the original book should be applied to the interpretation required at that time based on the translation corresponding to SIN(信), the translation corresponding to DAL(達) and the AH(雅) translation corresponding to the elegant interpretation. Translation is the most important purpose of implementing equivalence in the intentions of the original author, so the equivalence of the Source language and the Taget language should be observed even in the differences of expression. Up until now, the question of the translation of the nouns has mainly focused on the translation of the stylistic system by focusing on trying to overcome the structural differences of the language. Translation now requires the implementation of semantic equivalence as well as primarily a stylistic approach. This researcher wanted to open a new horizon for the study of classical literature in Myong-hak by presenting a standard for the translation of robes that achieve the intent and equivalence of the original author in the translation of the original text.

• Korean Journal of Cognitive Science
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• v.14 no.1
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• pp.29-40
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• 2003

Cross-Language Information Retrieval (CLIR) deals with the documents in various languages by one language query. A user who uses one language can retrieve the documents in another language through CLIR system. In CLIR, query translation method is known to be more efficient. For the better performance of query translation, we need more resources like dictionary, ontology, and parallel/comparable corpus but usually not available. This paper proposes a new concept called the Common Base Axis which is adapted to Korean-English Query translation ann a new weighting method in dictionary based query translation. The essential idea is that we can express Korean and English word in one vector space by Common Base Axis and use it in calculating sense distance for query weighting. The experiments show that Common Base Axis gives us good performance without ontology and is especially good for one word query translation.

• Annual Conference on Human and Language Technology
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• 1997.10a
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• pp.243-248
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• 1997

본 논문은 다국어 자동번역시스템에서 다국어의 번역지식(사전,규칙,정보)구축을 위해 언어유형론을 도입하는 방법론을 제안한다. 다국어 번역지식의 구축과 관련하여 기존 다국어 자동번역 시스템들에서 항상 문제가 되고 있는 것은 번역지식의 구축, 관리, 재활용의 문제이다. 번역지식의 구축은 다국어를 위한 번역지식의 크기, 다국어의 수용정도와 관련되며, 번역지식의 관리는 번역지식의 단순화 정도와 관련되며, 번역지식의 재활용은 기존에 구축된 번역지식을 새로운 언어들에 재사용 정도와 관련된다. 이러한 문제점들을 해결하기 위해 본 논문에서는 한국어를 포함한 다국어의 언어 친족성에 따라 번역지식을 공유하도록 하는 언어유형론에 기반한 다국어 공용 번역지식 구축 방법론을 제안하고자 한다.

• Proceedings of the Korean Society for Language and Information Conference
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• 1995.02a
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• pp.195-204
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• 1995

We propose a method to improve search time and space complexity in statistical machine translation architectures, by employing linguistic bracketing information on the source language sentence. It is one of the advantages of the probabilistic formulation that competing translations may be compared and ranked by a. principled measure, but at the same time, optimizing likelihoods over the translation spa.ce dictates heavy search costs. To make statistical architectures practical, heuristics to reduce search computation must be incorporated. An experiment applying our method to a prototype Chinese-English translation system demonstrates substantial improvement.

• Language and Information
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• v.3 no.1
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• pp.65-82
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• 1999

The interests in Machine Translation(MT) have gotten revitalized lately with the rapid expansion of internet users. MT technology has gone through several different stages of development, but the longest surviving methods usually maintains the following characteristics: the expand ability and flexibility based on proved linguistic formalism, the transfer method of translation, the continued efforts of systematic updates being made into the system. This paper introduces one such system, L&H Korean-English bidirectional MT system. This system uses Lexical-Functional Grammar as its linguistic framework. It also adopts the transfer method of MT and has been around on the market for over 10 years for other language pairs. Currently, the system covers over 10 different languages including Chinese, Japanese and Arabic, in addition to European languages. This paper will review the system in its core and discuss related tools and resources be ing used to enhance the quality of translation.