• Title/Summary/Keyword: Language engineering

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Korean Word Spacing System Using Syllable N-Gram and Word Statistic Information (음절 N-Gram과 어절 통계 정보를 이용한 한국어 띄어쓰기 시스템)

  • Choi, Sung-Ja;Kang, Mi-Young;Heo, Hee-Keun;Kwon, Hyuk-Chul
    • Annual Conference on Human and Language Technology
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    • 2003.10d
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    • pp.47-53
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    • 2003
  • 본 논문은 정제된 대용량 말뭉치로부터 얻은 음절 n-gram과 어절 통계를 이용한 한국어 자동 띄어쓰기 시스템을 제안한다. 한 문장 내에서 최적의 띄어쓰기 위치는 Viterbi 알고리즘에 의해 결정된다. 통계 기반 연구에 고유한 문제인 데이터 부족 문제, 학습 말뭉치 의존 문제를 개선하기 위하여 말뭉치를 확장하고 실험을 통해 얻은 매개변수를 사용하고 최장 일치 Viable Prefix를 찾아 어절 목록에 추가한다. 본 연구에 사용된 학습 말뭉치는 33,641,511어절로 구성되어 있으며 구어와 문어를 두루 포함한다.

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Bilingual lexicon induction through a pivot language

  • Kim, Jae-Hoon;Seo, Hyeong-Won;Kwon, Hong-Seok
    • Journal of Advanced Marine Engineering and Technology
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    • v.37 no.3
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    • pp.300-306
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    • 2013
  • This paper presents a new method for constructing bilingual lexicons through a pivot language. The proposed method is adapted from the context-based approach, called the standard approach, which is well-known for building bilingual lexicons using comparable corpora. The main difference between the standard approach and the proposed method is how to represent context vectors. The former is to represent context vectors in a target language, while the latter in a pivot language. The proposed method is very simplified from the standard approach thereby. Furthermore, the proposed method is more accurate than the standard approach because it uses parallel corpora instead of comparable corpora. The experiments are conducted on a language pair, Korean and Spanish. Our experimental results have shown that the proposed method is quite attractive where a parallel corpus directly between source and target languages are unavailable, but both source-pivot and pivot-target parallel corpora are available.

Construction of Knowledge Base for Question/Answering on Internet (인터넷 질의/응답을 위한 지식베이스 구축)

  • Chang, Moon-Soo;Jang, Myung-Gil;Kim, Hyun-Jin;Oh, Hyo-Jung;Lee, Jae-Sung
    • Annual Conference on Human and Language Technology
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    • 2000.10d
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    • pp.198-202
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    • 2000
  • 차세대 검색 엔진의 모형으로 일컬어지는 질의/응답 시스템을 개발하는데 있어서 보다 정확하고 유연한 검색 결과를 제공하기 위하여 개념망에 기반한 지식베이스 구축의 필요성이 대두되고 있다. 본 논문은 기존의 개념망에 속성 구조를 추가한 확장 개념망과 속성에 의해 분류되는 정답문서 집합으로 구성되는 지식베이스를 이용한 질의/응답 시스템을 제안한다. 본 논문의 지식베이스에서 정의한 속성은 질의/응답에서 정답문서를 효과적으로 연계시켜 사용자에게 보다 유연한 정답을 제공할 수 있게 한다. 본 논문에서는 경제 분야의 지식베이스의 활용예를 설명한다.

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Emotion Analysis of Characters in a Comic from State Diagram via Natural Language-based Requirement Specifications

  • Ye Jin Jin;Ji Hoon Kong;Hyun Seung Son;R. Young Chul Kim
    • International journal of advanced smart convergence
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    • v.13 no.1
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    • pp.92-98
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    • 2024
  • The current software industry has an emerging issue with natural language-based requirement specifications. However, the accuracy of such requirement analysis remains a concern. It is noted that most errors still occur at the requirement specification stage. Defining and analyzing requirements based on natural language has become necessary. To address this issue, the linguistic theories of Chomsky and Fillmore are applied to the analysis of natural language-based requirements. This involves identifying the semantics of morphemes and nouns. Consequently, a mechanism was proposed for extracting object state designs and automatically generating code templates. Building on this mechanism, I suggest generating natural language-based comic images. Utilizing state diagrams, I apply changes to the states of comic characters (protagonists) and extract variations in their expressions. This introduces a novel approach to comic image generation. I anticipate highly productive comic creation by applying software processes to Cartoon ART.

Burmese Sentiment Analysis Based on Transfer Learning

  • Mao, Cunli;Man, Zhibo;Yu, Zhengtao;Wu, Xia;Liang, Haoyuan
    • Journal of Information Processing Systems
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    • v.18 no.4
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    • pp.535-548
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    • 2022
  • Using a rich resource language to classify sentiments in a language with few resources is a popular subject of research in natural language processing. Burmese is a low-resource language. In light of the scarcity of labeled training data for sentiment classification in Burmese, in this study, we propose a method of transfer learning for sentiment analysis of a language that uses the feature transfer technique on sentiments in English. This method generates a cross-language word-embedding representation of Burmese vocabulary to map Burmese text to the semantic space of English text. A model to classify sentiments in English is then pre-trained using a convolutional neural network and an attention mechanism, where the network shares the model for sentiment analysis of English. The parameters of the network layer are used to learn the cross-language features of the sentiments, which are then transferred to the model to classify sentiments in Burmese. Finally, the model was tuned using the labeled Burmese data. The results of the experiments show that the proposed method can significantly improve the classification of sentiments in Burmese compared to a model trained using only a Burmese corpus.

Construction of Text Summarization Corpus in Economics Domain and Baseline Models

  • Sawittree Jumpathong;Akkharawoot Takhom;Prachya Boonkwan;Vipas Sutantayawalee;Peerachet Porkaew;Sitthaa Phaholphinyo;Charun Phrombut;Khemarath Choke-mangmi;Saran Yamasathien;Nattachai Tretasayuth;Kasidis Kanwatchara;Atiwat Aiemleuk;Thepchai Supnithi
    • Journal of information and communication convergence engineering
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    • v.22 no.1
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    • pp.33-43
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    • 2024
  • Automated text summarization (ATS) systems rely on language resources as datasets. However, creating these datasets is a complex and labor-intensive task requiring linguists to extensively annotate the data. Consequently, certain public datasets for ATS, particularly in languages such as Thai, are not as readily available as those for the more popular languages. The primary objective of the ATS approach is to condense large volumes of text into shorter summaries, thereby reducing the time required to extract information from extensive textual data. Owing to the challenges involved in preparing language resources, publicly accessible datasets for Thai ATS are relatively scarce compared to those for widely used languages. The goal is to produce concise summaries and accelerate the information extraction process using vast amounts of textual input. This study introduced ThEconSum, an ATS architecture specifically designed for Thai language, using economy-related data. An evaluation of this research revealed the significant remaining tasks and limitations of the Thai language.

Learning C Language Using Robots

  • Kim, Seung-Han;Jeon, Jae-Wook
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.119-122
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    • 2005
  • Lego company created a set called Robotic Invention System as a kind of Mindstorm set. This system helps to understand the technology of both robot and programming language. It also improves creativeness by building and controlling the robot we make. This paper will introduce basic idea of controlling the RCX(Programmable Lego Block) in C language. Also, this paper will show different idea of teaching C language by using other types of robots.

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A Transformation Method for Better C Code Based on Integration (통합에 기반한 더 좋은 C 코드로의 변환 방안)

  • Kim, Sung-ki
    • Journal of Engineering Education Research
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    • v.22 no.1
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    • pp.29-38
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    • 2019
  • Integration is an important intellectual ability to reconfigure several separated elements into one unified form and to concisely and categorically express them. In this paper, we classify the types of integration in C language, and propose a systematic and incremental method to transform to better code based on the integration types. This transformation method could also be used as a means to improve integrated thinking and efficiently learn C language, and will improve development ability in C programming or other language programming.

Design and Implementation of a Koran Text to Sign Language Translation System (한국어-수화 번역 시스템 설계)

  • Gwon, Gyeong-Hyeok;U, Yo-Seop;Min, Hong-Gi
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.3
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    • pp.756-765
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    • 2000
  • In this paper, a korean text to sign language translation system is designed and implemented for the hearing impaired people to learn letters and to have a conversation with normal people. We adopt the direct method for machine translation which uses morphological analysis and the dictionary search. And we define the necessary sign language dictionaries. Based on this processes, the system translate korean sentences to sign language moving picture. The proposed dictionaries are composed of the basic sign language dictionary, the compound sing language dictionary, and the resemble sign language dictionary. The basic sign language dictionary includes basic symbols and moving pictures of korean sign language. The compound sing language dictionary is composed of key-words of basic sign language. In addition, we offered the similar letters at the resemble sign language dictionary. The moving pictures of searched sign symbols are displayed on a screen in GIF formats by continuous motion of sign symbols or represented by the finger spelling based on the korean code analysis. The proposed system can provide quick sign language search and complement the lack of sign languages in the translation process by using the various sign language dictionaries which are characterized as korean sign language. In addition, to represent the sign language using GIF makes it possible to save the storage space of the sign language. In addition, to represent the sign language using GIF makes it possible to save storage space of the sign language dictionary.

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A Survey of Automatic Code Generation from Natural Language

  • Shin, Jiho;Nam, Jaechang
    • Journal of Information Processing Systems
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    • v.17 no.3
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    • pp.537-555
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    • 2021
  • Many researchers have carried out studies related to programming languages since the beginning of computer science. Besides programming with traditional programming languages (i.e., procedural, object-oriented, functional programming language, etc.), a new paradigm of programming is being carried out. It is programming with natural language. By programming with natural language, we expect that it will free our expressiveness in contrast to programming languages which have strong constraints in syntax. This paper surveys the approaches that generate source code automatically from a natural language description. We also categorize the approaches by their forms of input and output. Finally, we analyze the current trend of approaches and suggest the future direction of this research domain to improve automatic code generation with natural language. From the analysis, we state that researchers should work on customizing language models in the domain of source code and explore better representations of source code such as embedding techniques and pre-trained models which have been proved to work well on natural language processing tasks.