The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students

This project is to examine the accuracy of using existing speech recognition engine in interactive dialog system for English as second language (ESL) Malaysian primary school student in literacy education. Students are interested to learn literacy using computer that encompasses spoken dialog as it motivates students to be more confidence in reading and pronunciation without depending solely on teachers. This computer assisted learning will improve student’s oral reading ability by using the speech recognition in IDS. By using the system students are able to learn, to read and pronounce a word correctly independently without seeking help from teachers. This study is conducted at Sungai Berembang Primary School involving all 16 female and 18 male standard 2 students aged 8 years old. These students possess various reading pronunciation, abilities, and experience in English language with Malay language as their first language. The main objective of this studyis to examine the accuracy of using an existing speech recognition engine for ESL Malaysian students in literacy education. The specific objectives of this study are to identify requirement and evaluate speech recognition based dialog system for reading accuracy. This kind of speech recognition technology is aiming to provide teacher-similar tutoring ability in children’s phonemic awareness, vocabulary building, word comprehension, and fluent reading.This method has five stages. This method enables to construct a framework. Develop system architecture then analyze and design the system. It also builds the prototype for the system upon the system implementation which will be used in this study is the System Development Research Method.Lastly its observe, test the system and the results of the study and implementation of IDS students found 85% of this has helped the English language after using this system

Improving User Interaction with Spoken Dialog Systems via Shaping by

National Science Foundation. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government. iv Speech recognition technology offers an attractive interface option: speak to a computer, and it will understand you. One of the most promising applications of speech recognition technology is the spoken dialog system, which offers the promise of simple, direct, hands-free access to information. However, many factors conspire to make user communication with such a system less than optimally efficient. One problem is that users often speak beyond the bounds of what the computer is programmed to understand. This can lead to misunderstandings from the perspectives of both the user and the system, and recovering from such situations can add extra turns and time to the overall interaction. In this thesis, I describe a strategy, termed shaping, for improving user interaction efficiency with spoken dialo