• Title/Summary/Keyword: Vocabulary System

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A Study on the Phenomenological Centrality shown in Spatial Organization of Contemporary Architecture since 1960s (현대건축의 공간구성에서 나타나는 현상학적 중심성에 관한 연구)

  • Suh, Jeong-Yeon
    • Korean Institute of Interior Design Journal
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    • v.15 no.2 s.55
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    • pp.56-64
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    • 2006
  • From ancient times to today the formation of centrality in architecture has taken very important role as an organizing device. However after 19th century modem architecture focused on the universal aspect and homogeneity of space, and developed its own vocabulary through de-centralization. Since 1960's the reflections on de-humanized space of modem space have been evloved. As those movement has been understood seriously, the centrality can be changed to phenomenological one. And The phenomenological centrality maintains organic balance with its surroundings not trying to form a hierarchic system. So it shows human-oriented tendency and facilitates experiential movements of human body. And it also gives a sense of being. The phenomenological centrality is comprised of center, boundary, and two types of axis. The characteristics of phenomenological centrality can be analyzed as practical and meaningful center, visible boundary, experiential movement, and unexpectable encounters with spaces and nature.

Performance Evaluation of Large Vocabulary Continuous Speech Recognition System (대어휘 연속음성 인식 시스템의 성능평가)

  • Kim Joo-Gon;Chung Hyun-Yeol
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.99-102
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    • 2002
  • 본 논문에서는 한국어 대어휘 연속음성 인식 시스템의 성능향상을 위하여 Multi-Pass 탐색 방법을 도입하고, 그 유효성을 확인하고자 한다. 연속음성 인식실험을 위하여, 최근 실험용으로 널리 사용되고 있는 HTK와 Multi-Pass 탐색 방법을 이용한 음성인식 시스템의 비교 실험을 수행한다. 대어휘 연속음성 인식 시스템에 사용한 언어 모델은 ARPA 표준 형식의 단어 N-gram 언어모델로, 1-pass에서는 2-gram 언어모델을, 2-pass 에서는 역방향 3-gram 언어모델을 이용하여 Multi-Pass 탐색 방법으로 인식을 수행한다. 본 논문에서는 Multi-Pass 탐색 방법을 한국어 연속음성인식에 적합하게 구성한 후, 다양한 한국어 음성 데이터 베이스를 이용하여 인식실험을 수행하였다. 그 결과, 전화망을 통하여 수집된 잡음이 포함된 증권거래용 연속음성 데이터 베이스를 이용한 연속음성 인식실험에서 HTK가 $59.50\%$, Multi-Pass 탐색 방법을 이용한 시스템은 $73.31\%$의 인식성능을 나타내어 HTK를 이용한 연속음성 인식률 보다 약 $13\%$의 인식률 향상을 나타내었다.

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The Basic Study on making mono-phone for Korean Speech Recognition (한국어 음성 인식을 위한 mono-phone 구성의 기초 연구)

  • Hwang YoungSoo;Song Minsuck
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.45-48
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    • 2000
  • In the case of making large vocabulary speech recognition system, it is better to use the segment than the syllable or the word as the recognition unit. In this paper, we study on the basis of making mono-phone for Korean speech recognition. For experiments, we use the speech toolkit of OGI in U.S.A. The result shows that the recognition rate of :he case in which the diphthong is established as a single unit is superior to that of the case in which the diphthong is established as two units, i.e. a glide plus a vowel. And also, the recognition rate by the number of consonants is a little different.

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Implementation of Vocabulary-Independent Keyword Spotting System (가변어휘 핵심어 검출 시스템의 구현)

  • Shin Young Wook;Song Myung Gyu;Kim Hyung Soon
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.167-170
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    • 2000
  • 본 논문에서는 triphone을 기본단위로 하는 HMM에 의해 핵심어 모델을 구성하고, 사용자가 임의로 핵심어를 추가 및 변경할 수 있도록 가변어휘 핵심어 검출기를 구현하였다. 비핵심어 모델링 방법으로 monophone clustering을 사용한 방법 및 GMM을 사용한 방법의 성능을 비교하였다. 또한 후처리 과정에서 가변어휘 인식구조에 적합한 anti-subword 모델을 사용하였으며 몇 가지 구현방식에 따른 후처리 성능을 검토하였다. 실험결과 비핵심어 모델로 monophone을 clustering하여 사용한 방법보다 GMM을 사용한 경우 약간의 인식성능 개선을 얻을 수 있었으며, 후처리 과정에서 Kullback distance를 이용한 anti-subword 모델링 방식이 다른 방식에 비해 우수한 결과를 나타냈다.

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Proper Noun Embedding Model for the Korean Dependency Parsing

  • Nam, Gyu-Hyeon;Lee, Hyun-Young;Kang, Seung-Shik
    • Journal of Multimedia Information System
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    • v.9 no.2
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    • pp.93-102
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    • 2022
  • Dependency parsing is a decision problem of the syntactic relation between words in a sentence. Recently, deep learning models are used for dependency parsing based on the word representations in a continuous vector space. However, it causes a mislabeled tagging problem for the proper nouns that rarely appear in the training corpus because it is difficult to express out-of-vocabulary (OOV) words in a continuous vector space. To solve the OOV problem in dependency parsing, we explored the proper noun embedding method according to the embedding unit. Before representing words in a continuous vector space, we replace the proper nouns with a special token and train them for the contextual features by using the multi-layer bidirectional LSTM. Two models of the syllable-based and morpheme-based unit are proposed for proper noun embedding and the performance of the dependency parsing is more improved in the ensemble model than each syllable and morpheme embedding model. The experimental results showed that our ensemble model improved 1.69%p in UAS and 2.17%p in LAS than the same arc-eager approach-based Malt parser.

Constructing Japanese MeSH term dictionaries related to the COVID-19 literature

  • Yamaguchi, Atsuko;Takatsuki, Terue;Tateisi, Yuka;Soares, Felipe
    • Genomics & Informatics
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    • v.19 no.3
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    • pp.25.1-25.5
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    • 2021
  • The coronavirus disease 2019 (COVID-19) pandemic has led to a flood of research papers and the information has been updated with considerable frequency. For society to derive benefits from this research, it is necessary to promote sharing up-to-date knowledge from these papers. However, because most research papers are written in English, it is difficult for people who are not familiar with English medical terms to obtain knowledge from them. To facilitate sharing knowledge from COVID-19 papers written in English for Japanese speakers, we tried to construct a dictionary with an open license by assigning Japanese terms to MeSH unique identifiers (UIDs) annotated to words in the texts of COVID-19 papers. Using this dictionary, 98.99% of all occurrences of MeSH terms in COVID-19 papers were covered. We also created a curated version of the dictionary and uploaded it to Pub-Dictionary for wider use in the PubAnnotation system.

Learning English Vocabulary Using Synonyms And Antonyms System Design (동의어와 반의어를 활용한 영어 어휘 학습 시스템 설계)

  • Jun-Hyeok Ok;Hong-Jun Jang;Byoungwook Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.21-22
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    • 2023
  • 영어 공인 시험에서 영어 어휘는 가장 중요한 요소 중 하나이다. 그러나 기존 영어 어휘 학습 시스템은 단순히 어휘 교재의 콘텐츠를 디지털화한 것에 그치고 있다. 영어 어휘 학습에서 동의어에 대한 학습은 언어 능력을 향상시키고 다양한 상황에서 효과적으로 의사소통할 수 있는 능력 향상에 도움이 된다. 본 연구에서는 학습자들이 영어 어휘 학습을 효과적으로 할 수 있도록 동의어 및 반의어를 활용할 수 있는 학습 시스템을 제안한다. 본 시스템은 동의어와 반의어에 대한 정보가 필요한 영어 어휘를 입력으로 받아 생성형 AI에서 동의어 및 반의어에 대한 정보를 생성한 후에 반환하는 기능을 수행한다. 본 시스템은 학습자들이 어휘 평가에서 오답으로 답한 어휘에 대해 동의어 및 반의어에 대한 추가적인 어휘와 예문을 제공하여 영어 어휘 학습의 효율성을 높일 수 있을 것이다.

A Study on the Non-everydayness of Interior Object - Focused on Nigel Coates' Early Commercial Interior Design - (실내디자인에서 Object의 비일상성 연구 - Nigel Coates의 초기 상업공간작품을 중심으로 -)

  • Suh, Jeong-Yeon
    • Journal of the Korea Furniture Society
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    • v.23 no.2
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    • pp.185-194
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    • 2012
  • Contemporary society maintains mass-product system that keeps endless cycle of making and consuming. In this vein, everyday life becomes to be under the control of function and efficiency. On the contrary, the people are getting to have a desire of escaping from this everydayness, that is, the desire for non-everydayness. British architect, Nigel Coates understood the potentiality of contemporary metropolis which produce new experiences through their heterogeneities. During 1980s, Japanese economic bubble provided rich nourishment to the desire for non-everydayness based on consumers' tastes. Nigel Coates snatched this phenomena and designed commercial spaces aligned to the non-everydayness. He shows very eloquent version of escaping sense. We can find the exquisite quality of non-everydayness through design vocabulary of object's form and arrangement. In the viewpoint of object form, Coates adopted classical statues of Greek, that is antique, and modern gadgets such as airplane wings and seats. Also, we can find abundant gestures of curvilineal contours throughout the objects he designed. As for the objects' arrangement, he introduced repetition and curved composition that can stimulate human interaction with interior scape.

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Theory and practice of alphabetical subject indexing (주제색인의 이론과 실제)

  • 윤구호
    • Journal of Korean Library and Information Science Society
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    • v.10
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    • pp.95-131
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    • 1983
  • Index is a systematic guide to items contained in, or concepts derived from, a collection, Thus, it is represented as a paired set of index terms (t) and documents (D) : I= {(t,D) vertical bar t .mem. V, D .mem. W), where V is index vocabulary and W is document collection. Indexing is the process of analysing the informational content of records of knowledge and expressing the informational content in the language of the indexing system. It involves: 1) Selecting indexable concepts in a document; and 2) expressing these concepts in the language of the indexing system (as index entries): and an ordered list. Indexing process involves technical, semantic and syntactic problems. Technical problems are related to the accuracy of indexing, which is primarily governed by the indexer's ability of analysing subject, identifying indexable concepts, and coding. The proper levels of indexing exhaustivity, and index language specificity are also significant factors affecting the quality of index. Semantic problems are related to the choice of index terms and the form in which they should be used. Equivalent, hierarchical and affinitive/associative relationships of index terms are involved. Syntactic problems are largely related to the coordination of index terms. This process of coordination arises from the need to be able to search for the intersection of two or more classes defined by terms denoting distinct concepts. Finally, most valuable aspects of alphabetical subject indexing theories and practices are derived from those of Cutter, Kaiser, Ranganathan, Coates, Lynch and Austin, and discussed in details.

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Speech Recognition Error Compensation using MFCC and LPC Feature Extraction Method (MFCC와 LPC 특징 추출 방법을 이용한 음성 인식 오류 보정)

  • Oh, Sang-Yeob
    • Journal of Digital Convergence
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    • v.11 no.6
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    • pp.137-142
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    • 2013
  • Speech recognition system is input of inaccurate vocabulary by feature extraction case of recognition by appear result of unrecognized or similar phoneme recognized. Therefore, in this paper, we propose a speech recognition error correction method using phoneme similarity rate and reliability measures based on the characteristics of the phonemes. Phonemes similarity rate was phoneme of learning model obtained used MFCC and LPC feature extraction method, measured with reliability rate. Minimize the error to be unrecognized by measuring the rate of similar phonemes and reliability. Turned out to error speech in the process of speech recognition was error compensation performed. In this paper, the result of applying the proposed system showed a recognition rate of 98.3%, error compensation rate 95.5% in the speech recognition.