• English Language & Literature Teaching
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• v.16 no.3
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• pp.1-18
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• 2010

This study examined the effects of previewing and providing background knowledge on low level EFL readers' comprehension of expository texts and their responses to these treatments. 130 college freshmen were randomly placed into one of three treatment groups and read two expository texts reflecting unfamiliar cultural information. Prior to reading, one group was given previewing instruction, which included vocabulary preteaching and summaries, and a second group was provided with culture-specific background knowledge through watching videos and slides. The third group read each text without any prereading instruction. Immediately after reading a passage, subjects answered a 10-item multiple-choice test. Results showed significant positive effects of the previewing treatment and weak positive effects of the providing background knowledge treatment. Students' responses on the questionnaires revealed that the majority felt that the experimental treatments contributed to comprehension enhancement, made reading more enjoyable, and expedited their reading process. Students in the control group, however, indicated that they needed explicit prereading instruction in order to understand the texts. Pedagogical implications of the findings for EFL reading instruction are provided.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.21-32
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• 2021

The current study investigates how Malaysian ESL learners' L2 (English) speaking fluency is reflected in advanced L2 reading and what difficulties they encounter in reading comprehension. Nine Malaysian students attending a Korean university participated in qualitative research using in-depth and semi-structured interviews. The data revealed that L2 was a very familiar language, and their speaking fluency in L2 reduced the anxiety of L2 reading in general. However, it did not play a significant role in reading at an advanced level. Their difficulties in reading were mainly due to a lack of vocabulary knowledge. However, insufficient background knowledge and interest also frustrated their reading tasks. These factors lowered their reading comprehension, causing inaccurate interpretations or discouraging their endeavors to find messages from the given text. Thus, these findings should be carefully addressed in reading classes for Korean L2 learners as well as international students.

• Phonetics and Speech Sciences
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• v.14 no.3
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• pp.41-49
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• 2022

The average acoustic distribution of American English speakers was statistically compared with the English-speaking patterns of gifted students in a Science Academy in Korea. By analyzing speech recordings, the duration time of which is much longer than in previous studies, this research identified the degree of acoustic proximity between the two parties and the predictability of English academic achievement of gifted high school students. Long-term spectral acoustic power distribution vectors were obtained for 2,048 center frequencies in the range of 20 Hz to 20,000 Hz by applying an long-term average speech spectrum (LTASS) MATLAB code. Three more variables were statistically compared to discover additional indices that can predict future English academic achievement: the receptive vocabulary size test, the cumulative vocabulary scores of English formative assessment, and the English Speaking Proficiency Test scores. Linear regression and correlational analyses between the four variables showed that the receptive vocabulary size test and the low-frequency vocabulary formative assessments which require both lexical and domain-specific science background knowledge are relatively more significant variables than a basic suprasegmental level English fluency in the predictability of gifted students' academic achievement.

• Genomics & Informatics
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• v.19 no.3
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• pp.25.1-25.5
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• 2021

The coronavirus disease 2019 (COVID-19) pandemic has led to a flood of research papers and the information has been updated with considerable frequency. For society to derive benefits from this research, it is necessary to promote sharing up-to-date knowledge from these papers. However, because most research papers are written in English, it is difficult for people who are not familiar with English medical terms to obtain knowledge from them. To facilitate sharing knowledge from COVID-19 papers written in English for Japanese speakers, we tried to construct a dictionary with an open license by assigning Japanese terms to MeSH unique identifiers (UIDs) annotated to words in the texts of COVID-19 papers. Using this dictionary, 98.99% of all occurrences of MeSH terms in COVID-19 papers were covered. We also created a curated version of the dictionary and uploaded it to Pub-Dictionary for wider use in the PubAnnotation system.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.25-34
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• 2020

Community question and answering service is one of the main sources of information and knowledge in the Web. The quality of information in question and answer documents is determined by the clarity of the question and the relevance of the answers, and the readability of a document is a key factor for evaluating the quality. This study is to measure the quality of documents used in community question and answering service. For this purpose, we compare the frequency of occurrence by vocabulary level used in community documents and measure the readability index of documents by institution of author. To measure the readability index, we used the Dale-Chall formula which is calculated by vocabulary level and sentence length. The results show that the vocabulary used in the answers is more difficult than in the questions and the sentence length is longer. The gap in readability between questions and answers is also found by writing institution. The results of this study can be used as basic data for improving online counseling services.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2
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• pp.173-179
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• 2004

Due to the insufficiency of training data in large vocabulary continuous speech recognition, similar context dependent phones can be clustered by decision trees to share the data. When the decision trees are built and used to predict unseen triphones, a phonetic question set is required. The phonetic question set, which contains categories of the phones with similar co-articulation effects, is usually generated by phonetic or linguistic experts. This knowledge-based approach for generating phonetic question set, however, may reduce the homogeneity of the clusters. Moreover, the experts must adjust the question sets whenever the language or the PLU (phone-like unit) of a recognition system is changed. Therefore, we propose a data-driven method to automatically generate phonetic question set. Since the proposed method generates the phone categories using speech data distribution, it is not dependent on the language or the PLU, and may enhance the homogeneity of the clusters. In large vocabulary speech recognition experiments, the proposed algorithm has been found to reduce the error rate by 14.3%.

• English Language & Literature Teaching
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• v.13 no.4
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• pp.87-108
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• 2007

Given that various classroom contextual factors influence the nature of writing instructional practices, it would be worthwhile to explore these factors to generate better environment for learning to write. Among many factors, this study examined teachers' beliefs and knowledge, which would operate as a very influential contextual factor in that changes in principles and methods of teaching writing would be the results of their underlying beliefs and knowledge related to teaching writing. Three professional teachers who teach second- and third-grade English language learners (ELLs) were interviewed, and the analysis of teacher interviews was conducted. The research findings indicated that basically all of the teachers perceived the role of writing in second language learning as very important, sharing the belief that the ultimate goal of teaching writing is to have their students gain fluency in writing and that some of instructional methods such as integration of writing and other language aspects, content-based writing, and providing scaffolding are important. In addition, some beliefs that two ESL teachers shared included the importance of ample and continuous opportunities to write, vocabulary knowledge, and explicit instruction about writing. Other beliefs, including the importance of creating a comfortable writing environment and opportunities for writing for varied purposes and genres were represented.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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• pp.1297-1300
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• 2003

본 논문은 웹 온톨로지 데이터를 접근, 표현 및 처리 할 수 있는 온톨로지 객체 모델을 생성하기 위한 시스템이다. 시멘틱 웹의 대두로 인해 웹 상에 존재하는 데이터의 특성에 따라서 접근 할수 있는 방법도 다양화 되었다. 이에 웹 상에서 산재되어 있는 지식들을 가져와 각 도메인에 맞게 새로운 온톨로지를 생성하고 서로 다른 언어로 표현된 온톨로지를 계층 어휘들을 이용하여 시멘틱웹 환경에서 지식을 처리하기 위해 웹 온톨로지를 구축하고 처리할 수 있는 온톨로지 객체 모델을 제공하고, 온톨로지 객체 모델 API를 통해 외부 어플리케이션과의 정보를 교환한다. 본 논문에서는 웹 온톨로지를 표현하기 위한 모델을 계층별로 구별하여 프레임 기반의 상위 온톨로지(frame-based ontology layer), 다른 도메인에서도 사용이 가능한 공통된 어휘(vocabulary)를 표현한 핵심 온톨로지(generic ontology layer)와 각각의 온톨로지 언어에 의존적인 어휘를 표현한 기능 온톨로지(functional ontology layer)로 구성하여 표현의 중복을 없애고 재 사용성을 높이기 위한 모델을 제공함으로써, 온톨로지 추론, 병합 및 저작 도구 등의 외부 어플리케이션이 온톨로지 객체 모델에 손쉽게 접근할수 있고, 온톨로지에 대한 쉬운 지식 표현 및 핸들링을 제공할 수 있다.

• Phonetics and Speech Sciences
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• v.7 no.2
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• pp.29-38
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• 2015

This study explores reading fluency among elementary school students considering language level and family income(low SES). Forty eight students from 1st to 3rd grades participated in two paragraph reading tasks. Half of the children were from low income family and half of the children had low lexical knowledge. Reading fluency as in the number of correctly read syllables per minute, the total error frequency and error types were used to compare group differences. There were significant differences in the number of correctly read syllables per minute between two income groups and two language groups. There was a significant difference between low income group and non-low income group in total number of errors only when children's lexical knowledge were low. There were no group differences in error types of repetition and omission. Substitution and insertion error seemed to reflect the total error pattern. These results imply the importance of early screening and early involvement for children with low lexical knowledge from low income family. Monitoring and early intervention will support these children's reading development.