• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.217-223
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• 2009

Vocabulary recognition system of Mobile terminal is executed statistical method for vocabulary recognition and used statistical grammar recognition system using N-gram. If limit arithmetic processing capacity in memory of vocabulary to grow then vocabulary recognition algorithm complicated and need a large scale search space and many processing time on account of impossible to process. This study suggest vocabulary recognition optimize using MLHF System. MLHF separate acoustic search and lexical search system using FLaVoR. Acoustic search feature vector of speech signal extract using HMM, lexical search recognition execution using Levenshtein distance algorithm. System performance as a result of represent vocabulary dependence recognition rate of 98.63%, vocabulary independence recognition rate of 97.91%, represent recognition speed of 1.61 second.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.496-503
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• 2010

Speech recognition system is developed of standalone, In case of a mobile terminal using that low recognition rate represent because of limitation of memory size and audio compression. This study suggest vocabulary recognition highest performance improvement system for separate acoustic search and lexical search. Acoustic search is carry out in mobile terminal, lexical search is carry out in server processing system. feature vector of speech signal extract using GMM a phoneme execution, recognition a phoneme list transmission server using Lexical Tree Search algorithm lexical search recognition execution. System performance as a result of represent vocabulary dependence recognition rate of 98.01%, vocabulary independence recognition rate of 97.71%, represent recognition speed of 1.58 second.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.81-90
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• 2005

In this paper, we propose a novel approach which models multilingual story link detection by adapting the features such as timelines and multilingual spaces as weighting components to give distinctive weights to terms related to events. On timelines term significance is calculated by comparing term distribution of the documents on that day with that on the total document collection reported, and used to represent the document vectors on that day. Since two languages can provide more information than one language, term significance is measured on each language space and used to refer the other language space as a bridge on multilingual spaces. Evaluating the method on Korean and Japanese news articles, our method achieved $14.3{\%}\;and\;16.7{\%}$ improvement for mono- and multi-lingual story pairs, and for multilingual story pairs, respectively. By measuring the space density, the proposed weighting components are verified with a high density of the intra-event stories and a low density of the inter-events stories. This result indicates that the proposed method is helpful for multilingual story link detection.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.367-372
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• 2013

In general, Levenshtein distance algorithm have a problem with not distinguish the consideration of vacabulary retrieve, because Levenshtein methode is used to vocabulary order are not defined. In this paper, we propose a improved Levenshtein methode, it effectively manage the vocabulary retrieve by frequency use of a vocabulary, and it gives the weight number which have a order between vocabularies. Therefore proposed methode have a advantage of solve the defect of perception rate in the case of increase the vocabulary, improve the recognition time become higher and it can be effectively retrieval space management.. System performance as a result of represent vocabulary dependence recognition rate of 97.81%, vocabulary independence recognition rate of 96.91% in indoor environment. Also, vocabulary dependence recognition rate of 91.11%, vocabulary independence recognition rate of 90.01% in outdoor environment.

• Journal of Digital Convergence
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• v.13 no.2
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• pp.135-140
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• 2015

General CHMM vocabulary recognition system is model observation probability for vocabulary recognition of recognition rate's low. Used as the limiting unit is applied only to some problem in the phoneme model. Also, they have a problem that does not conform to the needs of the search range to meaning of the words in the vocabulary. Performs a phoneme recognition using GMM to improve these problems. We solve the problem according to the limited search words characterized by an improved k-means algorithm. Measure the effectiveness represented by the accuracy and reproducibility as compared to conventional system performance experiments. Performance test results accuracy is 83%p, and recall is 67%p.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.65-68
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• 2003

본 논문에서는 대화체 연속음성인식 과정에서 사용되는 다중발음사전의 개념을 확장하여 대화체 발화에 빈번하게 나타나는 불규칙한 발음변이 현상을 포용하도록 한 확장된 발음사전의 방법을 적용하여 대화체 연속음성인식에서 인식성능의 향상을 가져오게 됨을 실험을 통해 보여준다. 대화체 음성에서 빈번하게 나타나는 음운축약 및 음운탈락, 전형적인 오발화, 양성음의 음성음화 등의 발음변이는 언어모델의 효율성을 떨어뜨리고 어휘 수를 증가시켜 음성인식의 성능을 저하시키고, 또한 음성인식 결과로 나타나는 출력형태가 정형화되지 못하는 단점을 가지고 있다. 이에 이러한 발음변이들을 발음사전에 수용할 때 각각의 대표어휘에 대한 변이발음으로 처리하고, 언어모델과 어휘사전은 대표어휘만을 이용해 구성하도록 한다. 그리고, 음성인식기의 탐색부에서는 각각의 변이발음의 발음열도 탐색하되 대표어휘로 언어모델을 참조하도록 하고, 인식결과를 출력하도록 하여 결과적으로 인식성능을 향상시키고, 정형화된 출력패턴을 얻도록 한다. 본 연구에서는 어절단위 뿐 아니라 의사형태소[2] 단위의 발음사전에도 발음변이를 포용하도록 하여 실험을 하였다. 실험을 통해 어절단위의 다중발음사전 구성을 통해 ERR 10.9％, 의사형태소 단위의 다중발음 사전의 구성을 통해 ERR 4.3％의 성능향상을 보였다.

• Proceedings of the Korean Society for Information Management Conference
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• 1999.08a
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• pp.13-16
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• 1999

본 연구는 정보검색시스템에서의 이용자 인터페이스 효용성을 높이기 위하여 시도된 연구를 다각적으로 조사하였다. 특히 질의어처리 인터페이스, 탐색처리 인터페이스, 탐색수정 인터페이스를 중점으로 한 탐색관련 인터페이스 기능과 어휘 브라우즈, 이전 탐색 브라우즈, 탐색결과 브라우즈와 같은 브라우즈 관련 인터페이스 기능에 대하여 살펴보았다. 마지막으로 인터페이스의 새로운 기능과 앞으로의 경향도 기술하였다.

• Proceedings of the Korean Society for Information Management Conference
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• 2006.08a
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• pp.233-238
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• 2006

본 연구에서는 단어의 의미연상을 이용하여 시소러스를 작성해봄으로써 탐색 시소러스 구축에 있어 단어연상검사법의 적용가능성을 살펴보았다. 문헌정보학 분야를 대상으로 단어연상검사를 실시한 후 자극어와 반응어간의 의미관계를 파악하고 반응어와 통제어휘를 비교 분석하였다. 실험 및 분석결과, 단어연상검사를 이용하면 다양한 연관관계 용어들을 시소러스에 포함시킬 수 있으며, 통제어휘집에 나타난 하위관계와 동등관계 용어들을 어느 정도 반영할 수 있다는 것을 확인하였다. 단어의 의미연상을 이용하여 구축된 탐색 시소러스는 정보검색환경에서 질의확장에 응용될 수 있다.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1436-1443
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• 2010

In vocabulary recognition system has it's bad points of processing vocabulary unseen triphone and then no got distribution of confidence measure by cannot normalization. According to this problem to improve suggested VCOR(Version Control for Out-of Rejection) system by out-of vocabulary rejection algorithm use vocabulary management optimization and then phone data search support. In VCOR system to provide vocabulary information efficiently offering for user's vocabulary information using extend facet classification that improved for vocabulary measure management function offering accuracy of recognition for vocabulary. In this paper proposed system performance as a result of represent vocabulary dependence recognition rate of 97.56%, vocabulary independence recognition rate of 96.23%.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.22 no.4
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• pp.28-34
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• 2004

사건 탐색 및 추적(TDT: Topic Detection and Tracking) 연구 [1]은 전세계 각 나라에서 매일 보도 되고 있는 신문이나 방송 뉴스 기사에서 "어떤 중요한 사건이 발생했는가\ulcorner"또는 "새로운 사건이 일어났는가\ulcorner"와 같이 그날 처음 발생한 사건을 탐색하거나, 같은 사건을 다루는 기사들을 탐색하거나, 예전에 발생한 사건과 관련된 사건인지를 추적해 나가는 것이다.된 사건인지를 추적해 나가는 것이다.