The Implement of a Simple English Conversation System

• Main Authors: Chun-hung Wu, 吳俊宏
• Other Authors: Mu-Chun Su
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/48799924063740840383

碩士 === 國立中央大學 === 資訊工程學系碩士在職專班 === 100 === Learning a foreign language can connect one with the world, help him or her to communicate with the local community, increase the chance of finding a job or get a promotion, pass exams, etc. Among so many languages, English is a universal language which has been widely spoken by people in the world. With the advent of the global village, the need of the abilities of understanding English and speaking English fluently become very demanding. No matter who one is (e.g., a student, a business man, a tourist, etc), one may benefit by learning English. Learning English takes time and dedication. There are a lot of free or chargeable classes or web sources which can teach one to improve his or her English writing, listening and speaking capabilities. These courses may be group courses, individual courses, self-study textbooks, or on-line courses, and so on. The secret to learn English well is to put one into a real English living environment. Some people don''t feel comfortable in a classroom environment. Especially, one has to speak English in front of classmates whose mother language is the same as him or her. In addition, one may prefer to study at his or her own pace and when it suits him or her. This paper propose a simple English conversation platform based on the use of an existing network technology HTML5 and Google’s text to speech and voice recognition API tools. Via the simple English conversation platform, users can easily practice English conversation dialogues at his or her own pace and when it suits him or her. These conversation contents can be either ready-made or customized. During a pronunciation practice, the system will feedback a similarity degree message to users to inform them how good their pronunciations were after the system has recognized users’ speech content via the speech recognition API and the computation of the similarity between the correct sentence and the sentence spoken by the users. A new similarity measure is proposed in this thesis for the computation of the similarity degree. From the messages provided by the system, users may know how good they are in English conversations. This function will help users increase their self-confidence and ability in English conversations.