| Summary: | 碩士 === 國立暨南國際大學 === 資訊工程學系 === 96 === Chinese regard the full-scale learning and ability training more and more important since English e-Learning has been growing up in recent year. From early TOEFL test to nowadays GEPT and TOEIC examination, they have already included speaking to integrate English with the practicability and communication in our life. Now, training speaking skill becomes a major objective in English learning issue. With different reasoning on pronouncing system to native speakers, we usually speak the incorrect pronunciations that have caused some misunderstanding and difficulty of the communication when we talk to them.
Our thesis applies some related techniques of speech recognition and string alignment which are integrated to our web-based spoken English training system. First the speech recognition engine analyzes each word to get its time code. And then the alignment between our speech and text is deduced through Speech-Text Alignment with Dynamic Programming. We also employ the speech analysis of pitch tracking and syllable stress calculation for computing pitches. With these procedures, the audio timestamp and pitch of each word is obtained. Teachers can check and approve the analysis of student’s speech on this correction system and mark a variety of speaking mistakes on each word: syllable stress, pronunciation, liaison and intonation. We purpose a system that can help students correct their speaking and pronouncing on English through visualized annotations and it also has good effects on training native spoken English.
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