• 대한음성학회:학술대회논문집
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• 대한음성학회 2000년도 7월 학술대회지
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• pp.241-254
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• 2000

The past decade has witnessed the abundant use of computer in testing language skills such as listening and reading. Compared with these language skills, we have experienced little use of computer in testing a speaking skill including pronunciation. This is largely due to limitations of the current computer technology. One of such limitations for testing pronunciation is to store and automatically evaluate what the learner utters. Due to this limitation, the computer simply stores what the learner utters and raters evaluate it afterward on a certain rating continuum. With the advent of voice recognition technology, however, the computer has been able to test pronunciation in a systematic way. This technology enables the computer to identify, visually show, and evaluate the learner's intonation pattern by means of autocorrection. The evaluation is expressed in terms of the degree in which the learner's intonation pattern overlaps with that of the native speaker of the target language. In particular, the degree is numerically displayed on the screen, and this numeral is considered as the score of the learner's utterance under our testing framework.

• 경영과학
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• 제11권1호
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• pp.1-21
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• 1994

We usually use the simulation technique in the evaluation and the test of a design alternative of Automated Guided Vehicle System. In this paper, we introduce a simulation code generator which can assist simulation programmer in model development and programming. It consists of user interface, program editor, and program sorter. SIMAN is used as the target language.

• Journal of Information Processing Systems
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• 제12권3호
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• pp.455-467
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• 2016

This paper presents the constituent-based approach for aligning bilingual multiword expressions, such as noun phrases, by considering the relationship not only between source expressions and their target translation equivalents but also between the expressions and constituents of the target equivalents. We only considered the compositional preferences of multiword expressions and not their idiomatic usages because our multiword identification method focuses on their collocational or compositional preferences. In our experimental results, the constituent-based approach showed much better performances than the general method for extracting bilingual multiword expressions. For our future work, we will examine the scoring method of the constituent-based approach in regards to having the best performance. Moreover, we will extend target entries in the evaluation dictionaries by considering their synonyms.

• 반도체디스플레이기술학회지
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• 제10권1호
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• pp.113-118
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• 2011

This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• 아시아태평양코퍼스연구
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• 제5권1호
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• pp.1-21
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• 2024

This study aimed to identify target lexical bundles (e.g., on the other hand, at the same time) for argumentative essay writing and rank them in order of teaching priority for Japanese learners. Despite significant functional roles of lexical bundles in academic writing, the inclusion of lexical bundles in argumentative writing had been underexplored. Since argumentative writing skills help undergraduate students prepare for their academic careers (e.g., writing papers), the lexical bundles under this genre deserve more attention. This study first extracted 78 target bundles from L1 argumentative essay corpora (International Corpus Network of Asian Learners of English: ICNALE and Louvain Corpus of Native English Essays: LOCNESS). The study then classified the bundles according to their discourse functions and semantic transparency to estimate the learnability for Japanese learners in L2 compatible corpora with the ICNALE. The results showed that learners had difficulty using the bundles with referential functions (e.g., in the form of) and semantic opaqueness (e.g., when it comes to), suggesting that the bundles in these two categories should be prioritized among the 78 bundles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권1호
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• pp.108-118
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• 2009

In this paper we develop an indoor location tracking system and its 3D tracking monitoring viewer, viz., 3D Navigation Viewer (3DNV). We focus on the integration of an indoor location tracking system with the Virtual Reality Modeling Language (VRML), to facilitate a representation of the user's spatial information in virtual indoor environments that is synchronized with the physical location environment. The developed indoor location tracking system employs beacons as active transmitters, and a listener as a passive receiver. The distance information calculated from the difference speeds of RF and Ultrasonic signals is exploited, to determine the user's physical location. This is essential in supporting third parties like doctors and caregivers in identifying the activities and status of a particular individual via 3DNV. 3DNV serves as a unified user interface for an indoor location tracking system, showing the viewpoint and position of the target in virtual indoor environments. It was implemented using VRML, to provide an actual real time visualization of the target's spatial information.

• 영어어문교육
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• 제16권1호
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• pp.41-59
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• 2009

The present study investigated Korean learners' knowledge on the range of possible interpretations of English locative PPs with manner of motion verbs, and considers whether learners can arrive at a superset L2 grammar on the basis of positive L2 input. Unlike Korean, some English locative PPs occurring with manner of motion verbs (such as in John jumped on the bed) are ambiguous as they can be interpreted as either directional or locational. Thirty Korean learners of English in three distinct groups (Advanced EFL-only group; Intermediate-EFL-only group; and ESL-experienced group) participated in an experimental study, along with a control group of nine native speakers of English. The results of the study showed that I) Korean learners, overall, tended to interpret English locative PPs as only locational, failing to recognize the ambiguity between the directional and locational readings in the target structure; 2) For the learners who experienced only the EFL context, even highly proficient learners, as well as intermediate level learners, failed to acknowledge the ambiguity; 3) The learners who experienced the ESL context for an extended period of time could identify the target reading to some extent, although they still could not reach the native-like competence. From these results, it is argued that robustness of positive evidence, not simply its availability, is critical in the acquisition of the superset L2 targets like the present one.

• ETRI Journal
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• 제36권3호
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• pp.429-438
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• 2014

Semantic role labeling (SRL) is a task in natural-language processing with the aim of detecting predicates in the text, choosing their correct senses, identifying their associated arguments, and predicting the semantic roles of the arguments. Developing a high-performance SRL system for a domain requires manually annotated training data of large size in the same domain. However, such SRL training data of sufficient size is available only for a few domains. Constructing SRL training data for a new domain is very expensive. Therefore, domain adaptation in SRL can be regarded as an important problem. In this paper, we show that domain adaptation for SRL systems can achieve state-of-the-art performance when based on structural learning and exploiting a prior model approach. We provide experimental results with three different target domains showing that our method is effective even if training data of small size is available for the target domains. According to experimentations, our proposed method outperforms those of other research works by about 2% to 5% in F-score.

• 영어어문교육
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• 제16권4호
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• pp.239-265
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• 2010

This study investigates the effects of corpus-based vocabulary tasks on the acquisition of English vocabulary in an attempt to explore the influence of corpus use on EFL pedagogy. For this to be realized, a total of 40 Korean high school students participated in the study over a 4-week period. An experimental group used a set of corpus-based tasks for vocabulary learning, whereas a control group carried out a traditional task (i.e., the L1-L2 translation) for vocabulary learning. To assess learning gains, the students were asked to complete the pre- and post-treatment tests measuring the word form, meaning, and use aspects of target lexical items. Results of the study indicate that in the experimental group the corpus-based vocabulary tasks were beneficial for the learning of word forms and use. In particular, corpus-based benefits were greatest in the low-proficiency EFL learners' collocational aspects of vocabulary use. On the other hand, in the control group, the traditional vocabulary tasks benefited the meaning aspects of target vocabulary items the most. In addition, survey results revealed that most students were positive about the corpus-based learning experience although some expressed reservations about the heavy cognitive load and the time-consuming nature of the analysis of corpus data primarily due to learners' lack of language proficiency.

• 디지털콘텐츠학회 논문지
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• 제6권1호
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• pp.89-94
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• 2005

기계번역에서 자연어 생성의 목적은 입력언어의 어구 분석을 이용하여 그 문장의 의미를 변환해주는 목적 언어를 생성하는 것이다. 그것은 언어적 구조 낱말 전사. 대화체 언어, 어휘적 정보 등을 포함해야 한다. 본 연구에서는 대화체 자동 기계번역 시스템 구현계획의 일부인 음성, 음운 분야에서 담당하게 될 음성인식과 음성합성 알고리듬을 확립하기 위한 한국어 특질에 대한 기초조사를 하고자 한다. 또한 기계번역의 단계를 분석하여 형태소 분석 단계와 구문 분석 단계, 의미 분석 단계로 구분한다. 형태소 분석은 입력 문장을 받아 분리된 형태소를 사전 내에서 검색하여·품사 정보를 얻고 이웃하는 단어와의 접속 관계가 문법적으로 올바르게 되었는지를 점검한다. 본 연구의 결과가 대화체 기계번역 시스템 구현계획의 종합적 입장에서는 단순한 기초조사일 수 있지만, 한국어의 교육 및 기계번역 이해의 측면에서는 그 자체로 가치를 지닌다고 할 수 있겠다. 따라서 교육적 측면에서의 직접적 활용을 여러 측면에서 고려할 수 있을 것이다.