Hou-Chiang Tseng


2022

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The Design and Development of a System for Chinese Character Difficulty and Features
Jung-En Haung | Hou-Chiang Tseng | Li-Yun Chang | Hsueh-Chih Chen | Yao-Ting Sung
Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)

Feature analysis of Chinese characters plays a prominent role in “character-based” education. However, there is an urgent need for a text analysis system for processing the difficulty of composing components for characters, primarily based on Chinese learners’ performance. To meet this need, the purpose of this research was to provide such a system by adapting a data-driven approach. Based on Chen et al.’s (2011) Chinese Orthography Database, this research has designed and developed an system: Character Difficulty - Research on Multi-features (CD-ROM). This system provides three functions: (1) analyzing a text and providing its difficulty regarding Chinese characters; (2) decomposing characters into components and calculating the frequency of components based on the analyzed text; and (3) affording component-deriving characters based on the analyzed text and downloadable images as teaching materials. With these functions highlighting multi-level features of characters, this system has the potential to benefit the fields of Chinese character instruction, Chinese orthographic learning, and Chinese natural language processing.

2019

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基於階層式編碼架構之文本可讀性預測(A Hierarchical Encoding Framework for Text Readability Prediction)
Shi-Yan Weng | Hou-Chiang Tseng | Yao-Ting Sung | Berlin Chen
Proceedings of the 31st Conference on Computational Linguistics and Speech Processing (ROCLING 2019)

2018

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探索結合快速文本及卷積神經網路於可讀性模型之建立 (Exploring Combination of FastText and Convolutional Neural Networks for Building Readability Models) [In Chinese]
Hou-Chiang Tseng | Berlin Chen | Yao-Ting Sung
Proceedings of the 30th Conference on Computational Linguistics and Speech Processing (ROCLING 2018)

2017

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探究不同領域文件之可讀性分析 (Exploring Readability Analysis on Multi-Domain Texts) [In Chinese]
Hou-Chiang Tseng | Yao-Ting Sung | Berlin Chen
Proceedings of the 29th Conference on Computational Linguistics and Speech Processing (ROCLING 2017)

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探究使用基於類神經網路之特徵於文本可讀性分類 (Exploring the Use of Neural Network based Features for Text Readability Classification) [In Chinese]
Hou-Chiang Tseng | Berlin Chen | Yao-Ting Sung
International Journal of Computational Linguistics & Chinese Language Processing, Volume 22, Number 2, December 2017-Special Issue on Selected Papers from ROCLING XXIX

2016

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基於深層類神經網路及表示學習技術之文件可讀性分類(Classification of Text Readability Based on Deep Neural Network and Representation Learning Techniques)[In Chinese]
Hou-Chiang Tseng | Hsiao-Tsung Hung | Yao-Ting Sung | Berlin Chen
Proceedings of the 28th Conference on Computational Linguistics and Speech Processing (ROCLING 2016)

2015

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可讀性預測於中小學國語文教科書及優良課外讀物之研究(A Study of Readability Prediction on Elementary and Secondary Chinese Textbooks and Excellent Extracurricular Reading Materials) [In Chinese]
Yi-Nian Liu | Kuan-Yu Chen | Hou-Chiang Tseng | Berlin Chen
Proceedings of the 27th Conference on Computational Linguistics and Speech Processing (ROCLING 2015)