• Title/Summary/Keyword: Engineering in English

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Put English Title Here (새마을열차 환경소음 예측식 성능 비교에 관한 연구)

  • Cho, Jun-Ho;Koh, Hyo-In;Kim, Jae-Chul
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.11a
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    • pp.105-108
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    • 2007
  • Recently, due to the high interests for well being life, claims about noise ad vibration are increased very rapidly. Therefore more reliable and exact evaluation of noise impact has been required. Until now in Korea, only one prediction equation for the assessment of railway environmental noise was used. But that equation has many limits and weak points because of the update was not performed from 1993. So in this study, the performance of another equation proposed by authors was compared to the former. As a result, proposed prediction equation may be used to evaluate the impact of railway noise in the future.

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Digital Isolated Word Recognition System based on MFCC and DTW Algorithm (MFCC와 DTW에 알고리즘을 기반으로 한 디지털 고립단어 인식 시스템)

  • Zang, Xian;Chong, Kil-To
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.290-291
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    • 2008
  • The most popular speech feature used in speech recognition today is the Mel-Frequency Cepstral Coefficients (MFCC) algorithm, which could reflect the perception characteristics of the human ear more accurately than other parameters. This paper adopts MFCC and its first order difference, which could reflect the dynamic character of speech signal, as synthetical parametric representation. Furthermore, we quote Dynamic Time Warping (DTW) algorithm to search match paths in the pattern recognition process. We use the software "GoldWave" to record English digitals in the lab environments and the simulation results indicate the algorithm has higher recognition accuracy than others using LPCC, etc. as character parameters in the experiment for Digital Isolated Word Recognition (DIWR) system.

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Neural Model for Named Entity Recognition Considering Aligned Representation

  • Sun, Hongyang;Kim, Taewhan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.613-616
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    • 2018
  • Sequence tagging is an important task in Natural Language Processing (NLP), in which the Named Entity Recognition (NER) is the key issue. So far the most widely adopted model for NER in NLP is that of combining the neural network of bidirectional long short-term memory (BiLSTM) and the statistical sequence prediction method of Conditional Random Field (CRF). In this work, we improve the prediction accuracy of the BiLSTM by supporting an aligned word representation mechanism. We have performed experiments on multilingual (English, Spanish and Dutch) datasets and confirmed that our proposed model outperformed the existing state-of-the-art models.

Query Translation and Query Expansion Method in Korean-to-English Cross-Language Information Retreival (한영 교차언어 정보검색에서 질의 변환 및 질의 확장 방법)

  • Kim, Baeg-Il;Seo, Hee-Cheol;Rim, Hae-Chang
    • Annual Conference on Human and Language Technology
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    • 2002.10e
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    • pp.235-242
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    • 2002
  • 본 논문은 한영 교차언어 정보검색을 위한 질의 변환 방법과 질의 확장에 대해서 기술하고 있다. 한영 교차언어 정보 검색은 한국어 질의와 관련된 영어 문서를 검색하는 것을 말하며, 한국어 질의를 영어 질의로 변환하는 방법을 사용했다. 이를 위해 한국어 단어들에 대한 영어 대역어들의 공기 정보를 이용하며, 공기 정보로는 상호 정보를 사용했다. 또한 한국어와 영어의 연어 사전을 사용하여 성능을 향상시켰다. 추가적인 검색 성능 향상을 위한 방법으로, 기존 연구에서 많이 사용된 적합성 피드백에 의한 지역적 질의 확장 대신, 영어 워드넷을 확장하여 구축한 한영 이중언어 시소러스를 사용하여 질의 확장을 하는 전역적 질의 확장을 시도하였다. 실험결과, 정확률의 향상보다는 재현율의 향상 정도가 더 컸으며, 긴 질의보다 짧은 질의를 확장한 경우가 성능이 높았다.

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A Hierarchical Korean Word-order Generation in English-Korean Machine Translation (영한기계번역에서 계층적 한국어 어순 생성)

  • Seo, Jin-Won;Lee, Shin-Won;Chung, Sung-Jong;An, Dong-Un
    • Annual Conference on Human and Language Technology
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    • 2000.10d
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    • pp.303-308
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    • 2000
  • 본 논문에서는 영한기계번역 시스템에서 한국어 문장을 생성할 때 올바른 한국어 어순 규칙을 제안한다. 한국어 생성은 영한기계번역의 최종 단계로서 이전단계에서 얻어진 정보를 가지고 목적 언어인 한국어 문장을 만드는 곳이다. 본 논문에서 제안하는 계층적 어순 생성 규칙은 한국어 의존구조를 기본으로 하며 규칙 적용은 4가지 함수를 단계적으로 적용시킨다. 인터넷의 발달은 언어 장벽이라는 새로운 문제를 부각시켰으며 이를 위해서 기계번역은 활발히 연구가 진행되고 있는 분야이다. 한국어 문장에 대한 올바른 어순 생성 규칙은 번역 결과의 품질을 증가시키며, 기계 번역뿐만 아니라 한국어 생성을 필요로 하는 모든 시스템에 적용할 수 있다.

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A Study on Detection of Accentual Phrase's Boundaries according to Reading Speeds (낭독속도에 따른 강세구 경계 검출에 관한 연구)

  • Ju Jangkyu;Lee Kiyoung;Song Minsuck
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.91-94
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    • 2000
  • 최근 운율 구조와 문장구조 및 음운규칙과 관련 된 많은 언어학적 연구가 이루어져, 언어 이해 차원에서 의미 정보, 문장 구조 정보, discourse structure 등을 위한 운율 정보의 유용성이 입증되었으나, 이러한 결과가 최근의 음성인식 시스템에는 거의 적용되지 못하고 있다. 본 연구에서는 계층적인 방법을 기초로 하여 한국어의 연속음성으로부터 운율구를 검출하는 세그멘테이션법을 제안하였다. 우선, 입력된 음성으로부터 문장단위의 경계를 검출하기 위하여 휴지기를 이용하였으며 에너지, 휴지기의 지속시간 및 피치궤적을 참조하여 강세구의 경계를 검출하였다. 실험음성의 텍스트는 "만물상"이며, 남녀 각 2명의 표준어 화자가 빠른 속도와 보통 속도로 낭독한 음성데이터를 대상으로 비교하였다.

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Ranking Translation Word Selection Using a Bilingual Dictionary and WordNet

  • Kim, Kweon-Yang;Park, Se-Young
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.1
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    • pp.124-129
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    • 2006
  • This parer presents a method of ranking translation word selection for Korean verbs based on lexical knowledge contained in a bilingual Korean-English dictionary and WordNet that are easily obtainable knowledge resources. We focus on deciding which translation of the target word is the most appropriate using the measure of semantic relatedness through the 45 extended relations between possible translations of target word and some indicative clue words that play a role of predicate-arguments in source language text. In order to reduce the weight of application of possibly unwanted senses, we rank the possible word senses for each translation word by measuring semantic similarity between the translation word and its near synonyms. We report an average accuracy of $51\%$ with ten Korean ambiguous verbs. The evaluation suggests that our approach outperforms the default baseline performance and previous works.

A Hidden Markov Model Imbedding Multiword Units for Part-of-Speech Tagging

  • Kim, Jae-Hoon;Jungyun Seo
    • Journal of Electrical Engineering and information Science
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    • v.2 no.6
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    • pp.7-13
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    • 1997
  • Morphological Analysis of Korean has known to be a very complicated problem. Especially, the degree of part-of-speech(POS) ambiguity is much higher than English. Many researchers have tried to use a hidden Markov model(HMM) to solve the POS tagging problem and showed arround 95% correctness ratio. However, the lack of lexical information involves a hidden Markov model for POS tagging in lots of difficulties in improving the performance. To alleviate the burden, this paper proposes a method for combining multiword units, which are types of lexical information, into a hidden Markov model for POS tagging. This paper also proposes a method for extracting multiword units from POS tagged corpus. In this paper, a multiword unit is defined as a unit which consists of more than one word. We found that these multiword units are the major source of POS tagging errors. Our experiment shows that the error reduction rate of the proposed method is about 13%.

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English Title of The Paper (Times New Roman 12pt) (용융상태 알루미늄 소재의 유동제어 및 재활용 기술)

  • Hong K.D.;Kim K.D.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.10a
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    • pp.1020-1023
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    • 2005
  • The fluid flow and thermal analysis were carried out by using the finite element program, Ansys. In analysis process, a electromagnetic analysis was accomplished. In afterwards, Fluid and thermal analysis was done. Fluid flow and heat could be produced by electromagnetic pump. In other words, A magnetic field which electromagnetic pump generates influences Liquid Material(Al alloy). This paper calculates the fluid flow and temperature distribution according to time. Using material is Al alloy(A356).

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Construction of Vietnamese SentiWordNet by using Vietnamese Dictionary (베트남어 사전을 사용한 베트남어 SentiWordNet 구축)

  • Vu, Xuan-Son;Park, Seong-Bae
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.745-748
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    • 2014
  • SentiWordNet is an important lexical resource supporting sentiment analysis in opinion mining applications. In this paper, we propose a novel approach to construct a Vietnamese SentiWordNet (VSWN). SentiWordNet is typically generated from WordNet in which each synset has numerical scores to indicate its opinion polarities. Many previous studies obtained these scores by applying a machine learning method to WordNet. However, Vietnamese WordNet is not available unfortunately by the time of this paper. Therefore, we propose a method to construct VSWN from a Vietnamese dictionary, not from WordNet. We show the effectiveness of the proposed method by generating a VSWN with 39,561 synsets automatically. The method is experimentally tested with 266 synsets with aspect of positivity and negativity. It attains a competitive result compared with English SentiWordNet that is 0.066 and 0.052 differences for positivity and negativity sets respectively.