• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제9권2호
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• pp.53-60
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• 2020

감정분석은 문서 또는 대화상에서 주어진 주제에 대한 태도와 의견을 이해하는 과정이다. 감정분석에는 다양한 접근법이 있다. 그 중 하나는 감정사전을 이용하는 사전 기반 접근법이다. 본 논문에서는 널리 알려진 영어 감정사전인 VADER를 활용하여 한국어 감정사전을 자동으로 생성하는 방법을 제안한다. 제안된 방법은 세 단계로 구성된다. 첫 번째 단계는 한영 병렬 말뭉치를 사용하여 한영 이중언어 사전을 제작한다. 제작된 이중언어 사전은 VADER 감정어와 한국어 형태소 쌍들의 집합이다. 두 번째 단계는 그 이중언어 사전을 사용하여 한영 단어 그래프를 생성한다. 세 번째 단계는 생성된 단어 그래프 상에서 레이블 전파 알고리즘을 실행하여 새로운 감정사전을 구축한다. 이와 같은 과정으로 생성된 한국어 감정사전을 유용성을 보이려고 몇 가지 실험을 수행하였다. 본 논문에서 생성된 감정사전을 이용한 감정 분류기가 기존의 기계학습 기반 감정분류기보다 좋은 성능을 보였다. 앞으로 본 논문에서 제안된 방법을 적용하여 여러 언어의 감정사전을 생성하려고 한다.

• 한국의류산업학회지
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• 제14권2호
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• pp.211-221
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• 2012

The word 'chintz' is thought to be a corruption of spotted cloth. Printing remained a relatively primitive method of decorating textiles in Europe until the second half of the 17th century. The formation of the English East India Company sparked the influx into the West of painted and printed Indian cotton textiles. A William Sherwin took out the first English patent in 1676. The earlist European designs were florals in the Indian manner. Patterns of European flowers returned to England as birds, flowers, trees, vines and stained glass for Victorian chintz. In France, the original and most successsful manufacturer of the distinctive printed fabrics from Jouy was Christophe Philippe Oberkampf. Copperplate printing was introduced to Jouy in 1770, probably reaching the pinnacle of achievement in the craft after 1783 when Jean-Baptiste Huet became chief designer. Huet's style was widely imitated in France and abroad, and the term 'toile de Jouy' has come to be universally applied to monochrome figurative designs wherever and by whomsoever they were produced. Oberkampf served his apprenticeship as an engraver with some leading manufacturers, including a period in Mulhouse. In Alsace, which was not part of France until 1798, the first factory had opened in 1746 in Mulhouse, and the area soon had the largest number of print-works in France.

• 한국의류산업학회지
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• 제11권2호
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• pp.231-241
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• 2009

Embroidery is one of the oldest methods of textiles surface decoration. The masterpiece "Tapisserie de Bayeux," is one of the earliest Medieval embroideries. Embroidery was popular on a broad scale with introduction of what was called Opus Anglicanum("English work") in the 13th century. France had been producing sophisticated embroideries since the 16th century. England was the country producing the greatest quantity of embroideries of the best quality in the 17th century. Until the 17th century, the Church was the most important patron of needlework. Then a shift in emphasis occurred towards the domestic embroidery. English 17th century domestic embroidery reached a high point of technical brilliance and charm. In France, embroidery was produced on hangings as well as costume. 18th century interest in embellishing the domestic environment, embroideries became much more finely detailed than those of the 17th century with the use of finer wool and silk threads. French silk were the finest in the world, and their embroidery was arguably equally fine both in furnishing textiles and on costumes. "Art Needlework" was the major movement in embroidery in the late 19th century. The Royal School of Needlework was founded in 1872, followed by similar institutions around Britan. Splendid fashion embroidery of French haut-couture that was represented to Lesage atelier in 20th century.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1793-1801
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• 2016

Speech enhancement is a challenging problem due to the diversity of noise sources and their effects in different applications. The goal of speech enhancement is to improve the quality and intelligibility of speech by reducing noise. Many research works in speech enhancement have been accomplished in English and other European Languages. There has been limited or no such works or efforts in the past in the context of Tamil speech enhancement in the literature. The aim of the proposed method is to reduce the background noise present in the Tamil speech signal by using wavelets. New modified thresholding function is introduced. The proposed method is evaluated on several speakers and under various noise conditions including White Gaussian noise, Babble noise and Car noise. The Signal to Noise Ratio (SNR), Mean Square Error (MSE) and Mean Opinion Score (MOS) results show that the proposed thresholding function improves the speech enhancement compared to the conventional hard and soft thresholding methods.

• 한국음향학회지
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• 제31권5호
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• pp.298-308
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• 2012

This study was designed to examine the phoneme recognition errors of hearing-impaired (HI) listeners on a consonant-by-consonant basis, to show (1) how each HI ear perceives individual consonants differently and (2) how standard clinical measurements (i.e., using a tone and word) fail to predict these differences. Sixteen English consonant-vowel (CV) syllables of six signal-to-noise ratios in speech-weighted noise were presented at the most comfortable level for ears with mild-to-moderate sensorineural hearing loss. The findings were as follows: (1) individual HI listeners with a symmetrical pure-tone threshold showed different consonant-loss profiles (CLPs) (i.e., over a set of the 16 English consonants, the likelihood of misperceiving each consonant) in right and left ears. (2) A similar result was found across subjects. Paired ears of different HI individuals with identical pure-tone threshold presented different CLPs in one ear to the other. (3) Paired HI ears having the same averaged consonant score demonstrated completely different CLPs. We conclude that the standard clinical measurements are limited in their ability to predict the extent to which speech perception is degraded in HI ears, and thus they are a necessary, but not a sufficient measurement for HI speech perception. This suggests that the CV measurement would be a useful clinical tool.

• International Journal of Computer Science & Network Security
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• 제24권2호
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• pp.101-112
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• 2024

Telugu language is considered as fourth most used language in India especially in the regions of Andhra Pradesh, Telangana, Karnataka etc. In international recognized countries also, Telugu is widely growing spoken language. This language comprises of different dependent and independent vowels, consonants and digits. In this aspect, the enhancement of Telugu Handwritten Character Recognition (HCR) has not been propagated. HCR is a neural network technique of converting a documented image to edited text one which can be used for many other applications. This reduces time and effort without starting over from the beginning every time. In this work, a Unicode based Handwritten Character Recognition(U-HCR) is developed for translating the handwritten Telugu characters into English language. With the use of Centre of Gravity (CG) in our model we can easily divide a compound character into individual character with the help of Unicode values. For training this model, we have used both online and offline Telugu character datasets. To extract the features in the scanned image we used convolutional neural network along with Machine Learning classifiers like Random Forest and Support Vector Machine. Stochastic Gradient Descent (SGD), Root Mean Square Propagation (RMS-P) and Adaptative Moment Estimation (ADAM)optimizers are used in this work to enhance the performance of U-HCR and to reduce the loss function value. This loss value reduction can be possible with optimizers by using CNN. In both online and offline datasets, proposed model showed promising results by maintaining the accuracies with 90.28% for SGD, 96.97% for RMS-P and 93.57% for ADAM respectively.

• 한국산학기술학회논문지
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• 제5권1호
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• pp.21-25
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• 2004

This paper presents a typographical analyses and classes. Typographical analysis is an indispensable tool for machine-printed character recognition in English. This analysis is a preliminary step for character segmentation in OCR. This paper is divided into two parts. In the first part, word typographical classes from words are defined by the word typographical analysis. In the second part, character typographical classes from connected components are defined by the character typographical analysis. The character typographical classes are used in the character segmentation.

• 한국융합학회논문지
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• 제13권3호
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• pp.11-22
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• 2022

최근 교육 분야에서 다양한 인공지능 기술을 활용한 연구와 개발이 이뤄지고 있다. 인공지능을 활용한 교육 중 특히 대화형 에이전트는 시간과 공간의 제약을 받지 않고 음성인식, 번역과 같은 다양한 인공지능 기술과 결합해 더 효과적인 언어 학습을 가능하게 한다. 본 논문은 상용화된 교육용 플랫폼 중 이용자 수가 많고 영어 학습을 위한 대화형 에이전트가 활용된 플랫폼에 대한 동향 분석을 진행하였다. 동향 분석을 통해 현재 상용화된 교육용 플랫폼의 대화형 에이전트는 여러 한계점과 문제점이 존재했다. 구체적인 문제점과 한계점 분석을 위해 사전 학습된 최신 대용량 대화 모델과 비교 실험을 진행하였고, 실험 방법으로 대화형 에이전트의 대답이 사람과 비슷한지를 평가하는 Sensibleness and Specificity Average (SSA) 휴먼 평가를 진행하였다. 실험 내용을 바탕으로, 효과적인 학습을 위해 개선방안으로 대용량 파라미터로 학습된 대화 모델, 교육 데이터, 정보 검색 기능의 필요성을 제안했다.

• 한국융합학회논문지
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• 제9권10호
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• pp.45-53
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• 2018

최근 이중 언어 임베딩(bilingual word embedding) 관련 연구들이 각광을 받고 있다. 그러나 한국어와 특정 언어로 구성된 병렬(parallel-aligned) 말뭉치로 이중 언어 워드 임베딩을 하는 연구는 질이 높은 많은 양의 말뭉치를 구하기 어려우므로 활발히 이루어지지 않고 있다. 특히, 특정 영역에 사용할 수 있는 로컬 이중 언어 워드 임베딩(local bilingual word embedding)의 경우는 상대적으로 더 희소하다. 또한 이중 언어 워드 임베딩을 하는 경우 번역 쌍이 단어의 개수에서 일대일 대응을 이루지 못하는 경우가 많다. 본 논문에서는 로컬 워드 임베딩을 위해 한국어-영어로 구성된 한국 법률 단락 868,163개를 크롤링(crawling)하여 임베딩을 하였고 3가지 연결 전략을 제안하였다. 본 전략은 앞서 언급한 불규칙적 대응 문제를 해결하고 단락 정렬 말뭉치에서 번역 쌍의 질을 향상시켰으며 베이스라인인 글로벌 워드 임베딩(global bilingual word embedding)과 비교하였을 때 2배의 성능을 확인하였다.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1999년도 학술발표대회 논문집 제18권 2호
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• pp.361-364
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• 1999

한국어의 연속 음성 인식을 위하여 운율구 단위로 경계를 검출하는 연구가 진행되고 있다. 그 과정의 일부로서 본 연구에서는 여러 음향 특징들을 조합하여 연속음성에서 음절 경계의 검출하는 방법을 제시하였으며, 연속 음성으로부터 한국어 운율구인 강세구의 경계를 운율 특징만을 이용한 패턴 비교 방법을 이용하여 검출한 것과 비교 검토하였다. 그 결과, 패턴 비교 방법으로 검출한 강세구의 경계를 음절의 경계와 일치되도록 정렬해줄 필요가 있음을 알 수 있었다.