• Proceedings of the KSPS conference
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• 2003.10a
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• pp.175-179
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• 2003

In order to produce a high quality (intelligibility and naturalness) synthesized speech, it is very important to get an accurate grapheme-to-phoneme conversion and prosody model. In this paper, we analyzed Chinese texts using a segmentation, POS tagging and unknown word recognition. We present a grapheme-to-phoneme conversion using a dictionary-based and rule-based method. We constructed a prosody model using a probabilistic method and a decision tree-based error correction method. According to the result from the above analysis, we can successfully select and concatenate exact synthesis unit of syllables from the Chinese Synthesis DB.

• Annual Conference on Human and Language Technology
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• 1992.10a
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• pp.347-357
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• 1992

컴퓨터용어에 대한 약어들을 기존 사건관리 방법에서 벗어나 컴퓨터에 수록하여, 음성을 포함한 한글 및 영문풀이 조회, 추가등록, 삭제, 수정을 가능케 하여 어휘변화 및 의미파악에 신속히 대처하고, 영문, 한글 단어를 이용한 약어검색 기능과 시스템에서 임의로 문제를 출제, 학습자 수준을 측정해볼 수 있는 컴퓨터 보조학습(CAI)과 knowledge base 교체시 타분야에서 활용이 가능하도록 DB화한 약어 전문가체제로, 업무 활용자(학습자)와 컴퓨터 상호작용에 의한 개인차를 극복할 수 있도록 컴퓨터용어 약어 전자사전을 설계하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2073-2080
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• 2015

Even though users choose goods they want to buy in on-line shopping malls, real purchase is often performed in off-line shopping malls. It is called reverse showrooming. It means that users' analysis of goods based on images and description of internet shopping malls has limitation. Thus, large-scale online shopping malls provide a customized shopping information. However, in that case, the provided information is a simple list of goods users bought or retrieved. Thus, a system to analyze various needs of users and apply the result into on-line shopping mall is necessary. In this paper, an analysis system is proposed. The system contains a module to analyze user defined preference and a module to analyze users' reviews. The former designates two goods and collects preferences of individual users. the latter analyzes reviews about purchased goods based on database dictionary stored in advance for analyzing reviews. The system implemented shows that it is possible to recommend some goods that meet each users's needs

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.780-786
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• 2015

Social media, such as Social Network Service include a lot of spontaneous opinions from customers, so recent companies collect and analyze information about customer feedback by using the system that analyzes Big Data on social media in order to efficiently operate businesses. However, it is difficult to analyze data collected from online sites accurately with existing morpheme analyzer because those data have spacing errors and spelling errors. In addition, many online sentences are short and do not include enough meanings which will be selected, so established meaning selection methods, such as mutual information, chi-square statistic are not able to practice Emotional Classification. In order to solve such problems, this paper suggests a module that can revise the meanings by using initial consonants/vowels and phase pattern dictionary and meaning selection method that uses priority of word class in a sentence. On the basis of word class extracted by morpheme analyzer, these new mechanisms would separate and analyze predicate and substantive, establish properties Database which is subordinate to relevant word class, and extract positive/negative emotions by using accumulated properties Database.

• Journal of Navigation and Port Research
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• v.29 no.5 s.101
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• pp.457-464
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• 2005

Database integration has been recognized as a critical issue for effective logistics service in logistics environment. However, research related to effective methodology for this have been little studied, and also, prominent achievements have yet to be suggested. The aim of this paper is to present a quantitative methodology for the identification of conflict that is a representative problem on database integration. To achieve this aim, we suggested a quantitative methodology that can efficiently fine troubles such as name conflicts when schema integration, based on the level of semantic similarity between attributes and entities. And, in order to measure these semantic similarities, we used a thesaurus dictionary that proposed previous research. Finally, we presented effectiveness of the proposed methodology through some typical examples.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.251-260
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• 2008

In this paper, we present two verifier-based multi-party PAKE (password-authenticated key exchange) protocols. The shared key can be used for secure content transmission. The suggested protocols are secure against server compromise attacks. Our first protocol is designed to provide forward secrecy and security against known-key attacks. The second protocol is designed to additionally provide key secrecy against the server which means that even the server can not know the session keys of the users of a group. The suggested protocols have a constant number of rounds are provably secure in the standard model. To the best of our knowledge, the proposed protocols are the first secure multi-party PAKE protocols against server compromise attacks in the literature.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.81-85
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• 2002

We present a statistical analysis of Korean phonological variations using automatic generation of phonetic transcription. We have constructed the automatic generation system of Korean pronunciation variants by applying rules modeling obligatory and optional phonemic changes and allophonic changes. These rules are derived from knowledge-based morphophonological analysis and government standard pronunciation rules. This system is optimized for continuous speech recognition by generating phonetic transcriptions for training and constructing a pronunciation dictionary for recognition. In this paper, we describe Korean phonological variations by analyzing the statistics of phonemic change rule applications for the 60,000 sentences in the Samsung PBS(Phonetic Balanced Sentence) Speech DB. Our results show that the most frequently happening obligatory phonemic variations are in the order of liaison, tensification, aspirationalization, and nasalization of obstruent, and that the most frequently happening optional phonemic variations are in the order of initial consonant h-deletion, insertion of final consonant with the same place of articulation as the next consonants, and deletion of final consonant with the same place of articulation as the next consonants. These statistics can be used for improving the performance of speech recognition systems.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.21-30
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• 2019

Information about the formation and filling (in 2014 to 2016) of a terminological dictionary on electronics and radioengineering and collective work (in 2017 to 2018) with a data bank "TERMIN" is presented in this article. In purpose of creating an instrument of navigating the modern scientific-technical space a net of terms with set semantic links is described. This set is based on the analysis of terms' definitions (each term is checked for inclusion in the definitions of all other terms; the definitions were borrowed from reputable reference editions: encyclopedias, dictionaries, reference books). The created model of a system that consists of different information sources, in which it (information) is indexed by the terminology of Russian State Rubricator of Scientific and Technical Information rubrics and/or keywords, is described. There is an access for the search in all these sources in the system. Searching inquiries are referred to in the language of these rubrics or formulated by arbitrary terms. The system is to refer to information sources and give out relevant information. In accordance with this model, semantic links of various types, which allow expanding a search at different modalities of query, should be set among data bank terms. Obtained links will have to increase semantic matching, i.e., they can provide actual understanding of the meaning of the information that is being sought.

• The Journal of the Acoustical Society of Korea
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• v.21 no.7
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• pp.656-664
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• 2002

We present a statistical analysis of Korean phonological variations using a Grapheme-to-Phoneme (GPT) system. The GTP system used for experiments generates pronunciation variants by applying rules modeling obligatory and optional phonemic changes and allophonic changes. These rules are derived form morphophonological analysis and government standard pronunciation rules. The GTP system is optimized for continuous speech recognition by generating phonetic transcriptions for training and constructing a pronunciation dictionary for recognition. In this paper, we describe Korean phonological variations by analyzing the statistics of phonemic change rule applications for the 60,000 sentences in the Samsung PBS Speech DB. Our results show that the most frequently happening obligatory phonemic variations are in the order of liaison, tensification, aspirationalization, and nasalization of obstruent, and that the most frequently happening optional phonemic variations are in the order of initial consonant h-deletion, insertion of final consonant with the same place of articulation as the next consonants, and deletion of final consonant with the same place of articulation as the next consonant's, These statistics can be used for improving the performance of speech recognition systems.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.