Fluency Evaluation Aided by Mandarin Chinese Syntax for A Reading Assistant Robot

• Main Authors: Shin-Hau Huang, 黃信豪
• Other Authors: Jen-Hwa Guo
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/86127778268844969520

碩士 === 國立臺灣大學 === 工程科學及海洋工程學研究所 === 99 === The study investigates a fluency scoring technique for a reading assistance robot. The scoring technique is utilized for the evaluation of oral reading fluency to assist teachers by quantifying children’s reading achievement from children’ reading voices. The scoring of oral reading fluency could be used as a feedback when children are learning and it also can be regarded as a kind of evaluation tool to let the teachers or parents know the learning status of children. An automatic speech recognition system based on acoustic recognizer, language model and Chinese grammar based hierarchical hidden Markov model (CGBHHMM) is established. Acoustic model is trained by human pronunciation. Language model is trained to find the relationship between word and word from elementary school text book materials. CGBHHMM is a statistical model trained by the Chinese grammar tree structure. In the CGBHHMM, each sentence of acoustic syllabus is clustered into phrase production state, and CGBHHMM is then combined with ASR to detect a learner’s word accuracy. Five indicators, read speed, pause duration, pitch, stress and pronunciation, are considered as the features of oral reading fluency (ORF). The distance of ORF indicators is calculated of learners with respect to fluent teachers. These distances of ORF features were compared between fluent readers and foreigners who have learned Chinese for two years. It is verified that the proposed scoring method is effective to detect the fluency differences of fluent and influent readers. For future applications, oral reading fluency is could be used in real time by the assistance robot as feedback instructions to guide children for improving their reading achievement.