• Journal of Service Research and Studies
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• v.1 no.1
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• pp.113-122
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• 2011

In this research, we developed an practical service module as a application which operating on the smart phones based on the Android operating system. The service module supports on the voice processing function and inquiry windows also. After some documents and screens related on system analysis, service module are designed and implemented. The details about these modules are explained. We can expect to enhance the learning effects of english words memorizing competence for smart-phone users.

• Phonetics and Speech Sciences
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• v.1 no.3
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• pp.3-18
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• 2009

Do loanword properties emerge in the acquisition of a foreign language and if so, how? Classic studies in adult language learning assumed loanword properties that range from near-ceiling to near-chance level of appearance depending on speech proficiency. The present research argues that such variations reflect different phonological types, rather than speech proficiency. To investigate the difference between learner speech and loanword phonology, the current research analyzes the speech data from five different proficiency levels of 92 Korean speakers who read 19 pairs of English words and sentences that contained loanwords. The experimental method is primarily an acoustical one, by which the phonological cause in the loanwords (e.g., the insertion of [$\Box$] at the end of the word stamp) would be attested to appear in learner speech, in comparison with native speech from 11 English speakers and 11 Korean speakers. The data investigated for the research are of segment deletion, insertion, substitution, and alternation in both learner speech and the native speech. The results indicate that learner speech does not present the loanword properties in many cases, but depends on the types of phonological causes. The relatively easy acquisition of target pronunciation is evidenced in the cases of segment deletion, insertion, substitution, and alternation, except when the loanword property involves the successful command of the target phonology such as the de-aspiration of [p] in apple. Such a case of difficult learning draws a sharp distinction from the cases of easy learning in the development of learner speech, particularly beyond the intermediate level of proficiency. Overall, learner speech departs from loanword phonology and develops toward the native speech value, depending on phonological contrasts in the native and foreign languages.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.53-60
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• 2020

Sentiment analysis is the automated process of understanding attitudes and opinions about a given topic from written or spoken text. One of the sentiment analysis approaches is a dictionary-based approach, in which a sentiment dictionary plays an much important role. In this paper, we propose a method to automatically generate Korean sentiment lexicon from the well-known English sentiment lexicon called VADER (Valence Aware Dictionary and sEntiment Reasoner). The proposed method consists of three steps. The first step is to build a Korean-English bilingual lexicon using a Korean-English parallel corpus. The bilingual lexicon is a set of pairs between VADER sentiment words and Korean morphemes as candidates of Korean sentiment words. The second step is to construct a bilingual words graph using the bilingual lexicon. The third step is to run the label propagation algorithm throughout the bilingual graph. Finally a new Korean sentiment lexicon is generated by repeatedly applying the propagation algorithm until the values of all vertices converge. Empirically, the dictionary-based sentiment classifier using the Korean sentiment lexicon outperforms machine learning-based approaches on the KMU sentiment corpus and the Naver sentiment corpus. In the future, we will apply the proposed approach to generate multilingual sentiment lexica.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.71-76
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• 2019

The purpose of this study is to investigate the effect of action learning methods and practices, which have a research focus on learner-centered teaching after training students to use collaborative learning practices from the viewpoint that the learners acquire English skills through peer correction activities based on sociocultural learning theory[1]. From March 1, 2018 to June 15, 2018, one control class and one experimental group were selected from the general freshman English courses. The experimental group attended classes centered on collaborative writing activities using action learning and cooperation techniques, and the control group attended classes lecture style and rote learning methods to teach writing. The result of study has shown that, for the experimental group, there have been statistically significant results in the production of writing, such as the number of words, the number of sentences, and sentence length. Learners could share the knowledge or ideas of others in their learning relationships with more regular basis.

• The Journal of Economics, Marketing and Management
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• v.11 no.3
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• pp.47-66
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• 2023

Purpose: The purpose of this study is to identify research trends related to ESG by domestic and overseas researchers so far, and to present research directions and clues for the possibility of applying ESG to Korean companies in the future and ESG practice through comparison of derived topics. Research design, data and methodology: In this study, as of October 20, 2022, after searching for the keyword 'ESG' in 'scienceON', 341 domestic papers with English abstracts and 1,173 overseas papers were extracted. For analysis, word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and OLS regression analysis were performed to confirm trends for each topic using Python 3.7. Results: As a result of word frequency analysis, It was found that words such as management, company, performance, and value were commonly used in both domestic and overseas papers. In domestic papers, words such as activity and responsibility, and in overseas papers, words such as sustainability, impact, and development were included in the top 20 words. As a result of analyzing the co-occurrence frequency of words, it was confirmed that domestic papers were related mainly to words such as company, management, and activity, and overseas papers were related to words such as investment, sustainability, and performance. As a result of topic modeling, 3 topics such as named ESG from the corporate perspective were derived for domestic papers, and a total of 7 topics such as named sustainable investment for overseas papers were derived. As a result of the annual trend analysis, each topic did not show a relatively increasing or decreasing tendency, confirming that all topics were neutral. Conclusions: The results of this study confirmed that although it is desirable that domestic papers have recently started research on consumers, the subject diversity is lower than that of overseas papers. Therefore, it is suggested that future research needs to approach various topics such as forecasting future risks related to ESG and corporate evaluation methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.411-414
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• 2021

One of the elements of technology that has become extremely critical within the field of education today is Deep learning. It has been especially used in the area of natural language processing, with some word-representation vectors playing a critical role. However, some of the low-resource languages, such as Swahili, which is spoken in East and Central Africa, do not fall into this category. Natural Language Processing is a field of artificial intelligence where systems and computational algorithms are built that can automatically understand, analyze, manipulate, and potentially generate human language. After coming to discover that some African languages fail to have a proper representation within language processing, even going so far as to describe them as lower resource languages because of inadequate data for NLP, we decided to study the Swahili language. As it stands currently, language modeling using neural networks requires adequate data to guarantee quality word representation, which is important for natural language processing (NLP) tasks. Most African languages have no data for such processing. The main aim of this project is to recognize and focus on the classification of words in English, Swahili, and Korean with a particular emphasis on the low-resource Swahili language. Finally, we are going to create our own dataset and reprocess the data using Python Script, formulate the syllabic alphabet, and finally develop an English, Swahili, and Korean word analogy dataset.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.651-660
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• 2015

This study was conducted to consider application methods of infographic that corresponds to the educational goals of English subject, which is applied with different teaching and learning standards than other subjects. The aim of this study is to analyze the types and the characteristics of 'infographic completed by know-how learning', in other words, 'User behaviors involved infographic', which is frequently used in English textbook. Based on an analysis according to the teaching and learning standards, infographic used in English textbook were suggested in three types, which are 'General Concept', 'Significance' and 'Signification' centered infographic. In addition, according to the level of diagram composition, the main visualization attributes were derived as 'Overview', 'Structure', 'Relationships', 'Sequence', 'Transition between states' and 'Messages'. The major findings of this study are as follows: First, it is necessary to conduct a study on diverse display methods for 'Signification-centered infographic' that need to be displayed on the basis of two or more visual attributes. Second, as the purpose of application for applying infographic in English textbook collides with that in information design fields, it is found that verification is required on the educational effects in relation to this aspect.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.153-161
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• 2013

Recently, there has been a tremendous increase in the availability of educational materials for foreign language learning. As part of this trend, there has been an increase in the amount of electronically mediated materials available. However, conventional educational contents developed using computer technology has provided typically one-way information, which is not the most helpful thing for users. Providing the user's convenience requires additional off-line analysis for diagnosing an individual user's learning. To improve the user's comprehension of texts written in a foreign language, we propose an intelligent learning tool based on the analysis of the user's eyeball movements, which is able to diagnose and improve foreign language reading ability by providing necessary supplementary aid just when it is needed. To determine the user's learning state, we correlate their eye movements with findings from research in cognitive psychology and neurophysiology. Based on this, the learning tool can distinguish whether users know or do not know words when they are reading foreign language sentences. If the learning tool judges a word to be unknown, it immediately provides the student with the meaning of the word by extracting it from an on-line dictionary. The proposed model provides a tool which empowers independent learning and makes access to the meanings of unknown words automatic. In this way, it can enhance a user's reading achievement as well as satisfaction with text comprehension in a foreign language.

• Speech Sciences
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• v.5 no.2
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• pp.7-16
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• 1999

Starting as a poet, I learned about the sounds of words with David Abercrombie. Then, remembering my background in physics, I moved to studying acoustic phonetics and speech synthesis. From there I learned about psychology and how. to test perceptual theories. A meeting with a physiologist led to work on the use of the respiratory muscles in speech. Later I landed in Africa teaching English phonetics and learning about African languages. When I went to UCLA to set up a lab I was able to find bright students who helped make computer models of the vocal tract and taught me linguistic theory. And I was able to continue wandering around the world, describing the sounds of a wide range of languages.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.4
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• pp.163-170
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• 2019

Korea language has postpositions such as eul, reul, yi, ga, wa, and gwa, which are attached to nouns and add meaning to the sentence. When foreign notations or abbreviations are included in sentences, the appropriate postposition for the pronunciation of the foreign words may not be used. Sometimes, for natural expression of the sentence, two postpositions are used with one in parentheses as in "eul(reul)" so that both postpositions can be acceptable. This study finds examples of using unnatural postpositions when foreign words are included in Korean sentences and proposes a method for using natural postpositions by learning the final consonant pronunciation of nouns. The proposed method uses a recurrent neural network model to naturally express postpositions connected to foreign words. Furthermore, the proposed method is proven by learning and testing with the proposed method. It will be useful for composing perfect sentences for machine translation by using natural postpositions for English abbreviations or new foreign words included in Korean sentences in the future.