• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.9-16
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• 2016

The central goal of the current paper is to investigate lexical transfer between Korean and English and to identify rule-governed behavior and to provide implications for development of computer-assisted translation(CAT) software for the two languages. It will be shown that Sankoff and Poplack's Free Morpheme Constraint can not account for all the range of data. A constraint is proposed that a set of case-assigners such as verbs, INFL, prepositions, and the possessive marker may not undergo lexical transfer. The translation software is also expected to be equipped with the proposed claim that English verbs are actually borrowed as nouns or as defective verbs to escape from the direct attachment of inflectional morphemes.

• Cross-Cultural Studies
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• v.24
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• pp.84-98
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• 2011

This paper aims to analyze the influences of the socio-cultural environment on discourse in translation. To illustrate a deep connection between discourses and societies in which they were produced, communicative patterns of high- and low-context cultures are examined. Though the original version of the translated text comes from a different culture, the translation reflects communicative preferences of the target culture. To uncover some of these preferences, a comparative study of two translations from Russian into English and from English into Russian is conducted. This study, together with further investigation of some more recent translations into Russian, revealed a number of choices affected by translators' cultural background (for example, making the translation more emotionally charged) and current ideological preferences in the society (excessive use of anglicisms).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4835-4848
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• 2020

The recent expansion of the digital content market is increasing the technical demand for various facial image transformations within the virtual environment. The recent image translation technology enables changes between various domains. However, current image-to-image translation techniques do not provide stable performance through unsupervised learning, especially for shape learning in the face transition field. This is because the face is a highly sensitive feature, and the quality of the resulting image is significantly affected, especially if the transitions in the eyes, nose, and mouth are not effectively performed. We herein propose a new unsupervised method that can transform an in-wild face image into another face style through radical transformation. Specifically, the proposed method applies two face-specific feature loss functions for a generative adversarial network. The proposed technique shows that stable domain conversion to other domains is possible while maintaining the image characteristics in the eyes, nose, and mouth.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.144-150
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• 2023

With progressive advancements in Man-made consciousness (computer based intelligence) and Profound Learning (DL), contributing altogether to Normal Language Handling (NLP), the precision and nature of Machine Interpretation (MT) has worked on complex. There is a discussion, but that its no time like the present the human interpretation became immaterial or excess. All things considered, human flaws are consistently dealt with by its own creations. With the utilization of brain networks in machine interpretation, its been as of late guaranteed that keen frameworks can now decipher at standard with human interpreters. In any case, simulated intelligence is as yet not without any trace of issues related with handling of a language, let be the intricacies and complexities common of interpretation. Then, at that point, comes the innate predispositions while planning smart frameworks. How we plan these frameworks relies upon what our identity is, subsequently setting in a one-sided perspective and social encounters. Given the variety of language designs and societies they address, their taking care of by keen machines, even with profound learning abilities, with human proficiency looks exceptionally far-fetched, at any rate, for the time being.

• Communications of the Korean Mathematical Society
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• v.19 no.3
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• pp.519-529
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• 2004

M. Brown [2] posed an open question on the class of free homeomorphisms as follows: if f is a free homeomorphism of two manifold and k is a positive integer then is $f^{k}$ free\ulcorner In this paper we show that the answer of the open question is true.

• Journal of KIISE
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• v.44 no.2
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• pp.163-170
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• 2017

Despite the rise of studies in spoken to sign language translation, low-resource problems of sign language corpus have been rarely addressed. As a first step towards translating from spoken to sign language, we addressed the problems arising from resource scarcity when translating spoken language to manual signals translation using statistical machine translation techniques. More specifically, we proposed three preprocessing methods: 1) paraphrase generation, which increases the size of the corpora, 2) lemmatization, which increases the frequency of each word in the corpora and the translatability of new input words in spoken language, and 3) elimination of function words that are not glossed into manual signals, which match the corresponding constituents of the bilingual sentence pairs. In our experiments, we used different types of English-American sign language parallel corpora. The experimental results showed that the system with each method and the combination of the methods improved the quality of manual signals translation, regardless of the type of the corpora.

• Korean Journal of Cognitive Science
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• v.12 no.4
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• pp.11-27
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• 2001

Machine translation (MT) quality assessment is an outstanding problem. In the present situation in which the quality of machine-translated products are far from the user\\`s satisfaction objective evaluation of MT system is a prerequisite to building mutual trust between the users and the vendors stimulating constructive competition among the developers and finally leading to improve the quality of MT systems. Especially there emerges a need for an intensive study on how to evaluate the quality of MT systems from both linguistic and data processing aspects and to secure a steady improvement of the translation quality. With due regard to such points we in this paper present a linguistic evaluation of English-to-Korean machine translation based on a test suite composed of 3.373 sentences that were classified into their linguistic phenomena and complexity levels and report the experimental results made from several commercial MT systems.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.383-388
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• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.217-224
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• 2018

The aim of this study is to examine how satires in the English movie, are translated into Korean. Satire is a literary technique in which the writer expresses sarcasm or criticism by using humor or irony. As satire induces laughter by criticising someone or something in the form of humor, it is not easy to convey the same effect to audiences with different social, cultural and political backgrounds. Naturally, satire translation poses great challenge to translators. This study analyzed satirical humors in , based on 4 basic strategies discussed commonly in the previous studies on humor translation, which found out Source Text(ST) preservation prevails, that is to say literal translation. This analysis result is expected to be worth in drawing an effective strategy for satire translation in the convergence perspective of society, culture or politics in other countries.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.229-236
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• 2011

In this paper we present light weighted English-to-Korean and Korean-to-English mobile translators on smart phones. For natural translation and higher translation quality, translation engines are hybridized with Translation Memory (TM) and Rule-based translation engine. In order to maximize the usability of the system, we combined an Optical Character Recognition (OCR) engine and Text-to-Speech (TTS) engine as a Front-End and Back-end of the mobile translators. With the BLEU and NIST evaluation metrics, the experimental results show our E-K and K-E mobile translation equality reach 72.4% and 77.7% of Google translators, respectively. This shows the quality of our mobile translators almost reaches the that of server-based machine translation to show its commercial usefulness.