• Proceedings of the KSPS conference
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• 대한음성학회 1997년도 7월 학술대회지
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• pp.81-91
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• 1997

This paper deals with the problems of English listening comprehension: the rate of understanding difference in positions and sentence structures, parts of speech easily missed to understand, English sounds only in English(not in Korean), confusion of sounds, unaccented prefixes and suffixes, polysemy, homonym, juncture, understanding as one word by two different words, and sound blending in a normal speed of connected speech. Bearing those in mind I taught Suwon University freshmen video English with the mixed idea of Peterson's bottom-up and top-down methods putting in a meaningful context with thought group rather than word to word understanding. As a consequence, their errors come: prepositions, conjunctions, unstressed prefixes and suffixes, -ing from the present progressives and so forth. Assignments to have students transcribe the TV commercials and the names of reporters or Korean related news from English broadcastings are of use and help.

• Asia pacific journal of information systems
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• 제25권4호
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• pp.805-822
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• 2015

Online communities are an important source of electronic word-of-mouth (e-WOM). However, few studies have examined the use of such messages within the Middle Eastern context. This study focuses on Saudi women as members of an online beauty forum. Previous work suggested a mediating effect of gender, with women being more likely to trust word-of-mouth and follow it up with a purchase. A conceptual model with a theoretical underpinning from existing contributions in literature provides the basis of a coding framework for the message characteristics that influence members' e-WOM adoption. A total of 310 threads and 2200 messages coded into 5725 units were content analyzed to demonstrate cases where e-WOM was adopted and indicate further continuance intention with members returning to the forum. A new category of 'community bonding' was created from the content analysis given the prevalence of emotional aspects in messages. Emotion expressed in messages, often expressed in religious terms, is as influential and important as the cognitive aspects of community bonding.

• Proceedings of the KIEE Conference
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• 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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• pp.290-291
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• 2008

The most popular speech feature used in speech recognition today is the Mel-Frequency Cepstral Coefficients (MFCC) algorithm, which could reflect the perception characteristics of the human ear more accurately than other parameters. This paper adopts MFCC and its first order difference, which could reflect the dynamic character of speech signal, as synthetical parametric representation. Furthermore, we quote Dynamic Time Warping (DTW) algorithm to search match paths in the pattern recognition process. We use the software "GoldWave" to record English digitals in the lab environments and the simulation results indicate the algorithm has higher recognition accuracy than others using LPCC, etc. as character parameters in the experiment for Digital Isolated Word Recognition (DIWR) system.

• Annual Conference on Human and Language Technology
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• 한국정보과학회언어공학연구회 2018년도 제30회 한글 및 한국어 정보처리 학술대회
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• pp.504-509
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• 2018

Neural machine translation (NMT) has recently achieved the state-of-the-art performance. However, it is reported failing in the word sense disambiguation (WSD) for several popular language pairs. In this paper, we explore the extent to which NMT systems are able to disambiguate the Korean homographs. Homographs, words with different meanings but the same written form, cause the word choice problems for NMT systems. Consistent with the popular language pairs, we discover that NMT systems fail to translate Korean homographs correctly. We provide a Korean word sense disambiguation tool-UTagger to use for improvement of NMT's translation quality. We conducted translation experiments using Korean-English and Korean-Vietnamese language pairs. The experimental results show that UTagger can significantly improve the translation quality of NMT in terms of the BLEU, TER, and DLRATIO evaluation metrics.

• Korean Journal of Child Studies
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• 제29권3호
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• pp.357-373
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• 2008

This study compared the writing of Korean and Korean-Chinese adolescents using K-LIWC (Korean-Linguistic Inquiry Word Count Lee & Yoon, 2005). Three hundred ten (70 : Ulsan, Korea 90 : Yanji, and 150 : Shenyang, China) middle school students wrote a self introductory essay for unknown friends. K-LIWC yielded counts and percentages of word categories using the parts of speech of the Korean language and psychological (emotional, cognitive, sensory/perceptual, social, physical/functional and metaphysical processes) criteria. Results showed that use of pre-noun and present tense correlated with negative mood of the subjects. The writings of Korean-Chinese in Shenyang showed the most negative emotions among the three groups. This was interpreted to be a reflection of better protective factors for Korean-Chinese adolescents in Yanji compared with Shenyang.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.281-281
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• 2000

This paper presents an implementation of speech recognition system for teaching an autonomous mobile robot. The use of human speech as the teaching method provides more convenient user-interface for the mobile robot. In this study, for easily teaching the mobile robot, a study on the autonomous mobile robot with the function of speech recognition is tried. In speech recognition system, a speech recognition algorithm using HMM(Hidden Markov Model) is presented to recognize Korean word. Filter-bank analysis model is used to extract of features as the spectral analysis method. A recognized word is converted to command for the control of robot navigation.

• Genomics & Informatics
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• 제17권3호
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• pp.25.1-25.6
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• 2019

Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Herein, we conduct a statistical analysis of the publications of Genomics & Informatics over the 16 years since its inception, with a particular focus on issues relating to article categories, word clouds, and the most-studied genes, drawing on recent reviews of the use of word frequencies in journal articles. Trends in the studies published in Genomics & Informatics are discussed both individually and collectively.

• Journal of Advanced Marine Engineering and Technology
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• 제38권4호
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• pp.444-450
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• 2014

Most researches on word sense disambiguation have used static sized context regardless of sentence patterns. This paper proposes to use dynamic sized context considering sentence patterns and distance between words for word sense disambiguation. We evaluated our system 12 words in 32,735sentences with Sejong POS and sense tagged corpus, and dynamic sized context showed 92.2% average accuracy for predicates, which is better than accuracy of static sized context.

• Speech Sciences
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• 제7권4호
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• pp.169-186
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• 2000

This paper aims to confirm the mispronunciation of native Korean students due to the phonetic and phonological system differences between English and Korean, and to find the works-to-do by experiment. Many Korean students tend to differentiate the sounds of word-final stop consonants not by vowel duration or the allophones but by the phoneme of the consonant itself. In English, Stop sounds change through the conditions of the aspirated, unaspirated, or unreleased sounds. But in Korean they are not allophones of phonemes but distinct phonemes. Therefore, many Korean students are apt to add an extra vowel sound /i/ after the final stop consonant in the eve form due to both the unperception of the differences between the phonemes and the allophones of stop consonants, and the influence of the Korean sound-sequence relationship. Since the replacement of the allophones and extra vowel addition does not change the meaning, the importance was almost lost. Nevertheless, this kind of study is essential for the precise learning and the use of the English language.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2180-2197
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• 2019

With the proliferation of the Android malicious applications, malware becomes more capable of hiding or confusing its malicious intent through the use of code obfuscation, which has significantly weaken the effectiveness of the conventional defense mechanisms. Therefore, in order to effectively detect unknown malicious applications on the Android platform, we propose DroidVecDeep, an Android malware detection method using deep learning technique. First, we extract various features and rank them using Mean Decrease Impurity. Second, we transform the features into compact vectors based on word2vec. Finally, we train the classifier based on deep learning model. A comprehensive experimental study on a real sample collection was performed to compare various malware detection approaches. Experimental results demonstrate that the proposed method outperforms other Android malware detection techniques.