CRIE: An automated analyzer for Chinese texts

Yao Ting Sung, Tao Hsing Chang, Wei Chun Lin, Kuan Sheng Hsieh, Kuo En Chang

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Textual analysis has been applied to various fields, such as discourse analysis, corpus studies, text leveling, and automated essay evaluation. Several tools have been developed for analyzing texts written in alphabetic languages such as English and Spanish. However, currently there is no tool available for analyzing Chinese-language texts. This article introduces a tool for the automated analysis of simplified and traditional Chinese texts, called the Chinese Readability Index Explorer (CRIE). Composed of four subsystems and incorporating 82 multilevel linguistic features, CRIE is able to conduct the major tasks of segmentation, syntactic parsing, and feature extraction. Furthermore, the integration of linguistic features with machine learning models enables CRIE to provide leveling and diagnostic information for texts in language arts, texts for learning Chinese as a foreign language, and texts with domain knowledge. The usage and validation of the functions provided by CRIE are also introduced.

Original languageEnglish
Pages (from-to)1238-1251
Number of pages14
JournalBehavior Research Methods
Volume48
Issue number4
DOIs
Publication statusPublished - 2016 Dec 1

Keywords

  • CRIE
  • Chinese text analysis
  • Linguistic feature
  • Readability

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Psychology (miscellaneous)
  • Psychology(all)

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