• Korean Journal of Cognitive Science
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• v.15 no.2
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• pp.43-53
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• 2004

The purpose of this study was to investigate the role of phonology in lexical access of bilingual processing for Korean-English bilinguals. Four experiments have been conducted in order to adjudicate the nonselective lexical access hypothesis, which argues simultaneous phonological activation of two bilingual languages, and the selective lexical access hypothesis. which argues phonological activation of only one bilingual language. The results showed that the Korean target word processing was significantly affected by the phonological manipulation of the English target word(Exp. 2). Similarly, the English target word processing showed the tendencies that it is affected by the phonological manipulation of the Korean prime word(Exp. 2). This results indicates that the phonological information of another bilingual language is automatically activated when we process one of bilingual languages, and the process of English which is the second language for most Korean, is phonologically activated.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.805-817
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• 2017

Cross-lingual query expansion is usually based on the relationship among monolingual words. Bilingual comparable corpus contains relationships among bilingual words. Therefore, this paper proposes a method based on these relationships to conduct query expansion. First, the word vectors which characterize the bilingual words are trained using Chinese and Thai bilingual comparable corpus. Then, the correlation between Chinese query words and Thai words are computed based on these word vectors, followed with selecting the Thai candidate expansion terms via the correlative value. Then, multi-group Thai query expansion sentences are built by the Thai candidate expansion words based on Chinese query sentence. Finally, we can get the optimal sentence using the Chinese and Thai query expansion method, and perform the Thai query expansion. Experiment results show that the cross-lingual query expansion method we proposed can effectively improve the accuracy of Chinese and Thai cross-language information retrieval.

• Journal of Information Processing Systems
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• v.4 no.4
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• pp.121-132
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• 2008

VLSI chips have been tested using various automatic test equipment (ATE). Although each ATE has a similar structure, the language for ATE is proprietary and it is not easy to convert a test program for use among different ATE vendors. To address this difficulty we propose a tester structure expression language, a tester language with a novel format. The developed language is called the general tester language (GTL). Developing an interpreter for each tester, the GTL program can be directly applied to the ATE without conversion. It is also possible to select a cost-effective ATE from the test program, because the program expresses the required ATE resources, such as pin counts, measurement accuracy, and memory capacity. We describe the prototype environment for the GTL and the tester selection tool. The software size of the prototype is approximately 27,800 steps and 15 manmonths were required. Using the tester selection tool, the number of man-hours required in order to select an ATE could be reduced to 1/10. A GTL program was successfully executed on actual ATE.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.552-554
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• 2019

Deaf mutism (a hearing-impaired person and speech disorders) communicates using sign language. There are difficulties in communicating by voice. However, sign language can only be limited in communicating with people who know sign language because everyone doesn't use sign language when they communicate. In this paper, a finger language translation system is proposed and implemented as a means for the disabled and the non-disabled to communicate without difficulty. The proposed algorithm recognizes the finger language data by leap motion and self-learns the data using machine learning technology to increase recognition rate. We show performance improvement from the simulation results.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.239-245
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• 2019

Recently, effort to obtain various information from the vast amount of social network services (SNS) big data generated in daily life has expanded. SNS big data comprise sentences classified as unstructured data, which complicates data processing. As the amount of processing increases, a rapid processing technique is required to extract valuable information from SNS big data. We herein propose a system that can extract human sentiment information from vast amounts of SNS unstructured big data using the naïve Bayes algorithm and natural language processing (NLP). Furthermore, we analyze the effectiveness of the proposed method through various experiments. Based on sentiment accuracy analysis, experimental results showed that the machine learning method using the naïve Bayes algorithm afforded a 63.5% accuracy, which was lower than that yielded by the NLP method. However, based on data processing speed analysis, the machine learning method by the naïve Bayes algorithm demonstrated a processing performance that was approximately 5.4 times higher than that by the NLP method.

• Journal of Computing Science and Engineering
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• v.3 no.3
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• pp.143-164
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• 2009

This article surveys recent research in the area of language modeling (sometimes called statistical language modeling) approaches to information retrieval. Language modeling is a formal probabilistic retrieval framework with roots in speech recognition and natural language processing. The underlying assumption of language modeling is that human language generation is a random process; the goal is to model that process via a generative statistical model. In this article, we discuss current research in the application of language modeling to information retrieval, the role of semantics in the language modeling framework, cluster-based language models, use of language modeling for XML retrieval and future trends.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.235-238
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• 1989

Generally, Industrial robots are often controlled using joint processors and treating each joint as an independent servo loop. This paper presents a system architecture for robot control designed for real-time control of motion and sensory processing utilizing general-purpose Personal Computer. And for easily use and system expendability, robot language is implemented with C-language as base language. Through this system user can easily update robot language by design of his own language primitives. This system also don't require another development tool and can be used as advanced algorithm simulator in robotics laboratories.

• Korean Journal of English Language and Linguistics
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• v.2 no.3
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• pp.373-401
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• 2002

It is often observed that Korean migrant students overseas experience various kinds of anxieties learning English as a second language although they are in an English-speaking country like New Zealand. The context of learning English as a second language is explored by examining language anxieties experienced by recent Korean migrant students in New Zealand. 177 students were surveyed using questionnaires asking their anxieties over various contexts of English learning processes. The three stages of language anxiety of Input, Processing, and Output showed that there were some degrees of anxiety among the students at each stage depending on their ages, age at migration, and duration of residence, in particular. Students tended to experience more language anxiety in school than outside the school. It was also clear that students were experiencing more anxieties with English than with Korean in the four language skills of speaking, listening, reading and writing. Writing was commonly found in English and Korean to be the most frequent source of anxiety among the four language skills. Some implications from the results are suggested for parents, teachers, and students.

• Annual Conference on Human and Language Technology
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• 1999.10d
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• pp.3-5
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• 1999

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.75-78
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• 2000

본 논문은 자연스러운 합성음 생성을 위한 끊어 읽기 강도 예측에 관한 것으로, 문장에 대한 품사열이 주어졌을 때 Posteriori 확률을 최대화하는 끊어 읽기 강도를 비터비 디코딩으로 예측한다. 훈련용 데이터는 여성화자 1인이 발성한 2,100 문장이며, 음성 데이터로부터 휴지길이(pause)에 따라 끊어 읽기 강도를 2단계로 할당하고, 텍스트에서는 30개의 품사 태그 심볼을 이용하여 형태소분석 및 태깅을 수행하였다. 관측확률은 3개 연속하는 품사열이 발생할 확률로 하고 끊어 읽기 강도 천이확률은 bigram으로 했을 때, cross validation 방법으로 성능 평가를 수행하였다 평가결과, 훈련데이타에 대해서는 $89.7\%$, 테스트 데이터에 대해서는 $84.9\%$의 예측정확률을 보였다.