Speech Analyser in an ICAI System for TESOL
Huayang Xie · 2004
There is an increasing demand for computer software which can provide useful personalised feedback to English as a Second Language (ESL) speakers on prosodic aspects of their speech, to supplement the shortage of ESL teachers and reduce the cost of learning. This thesis concentrates on constructing such an Intelligent Computer Aided Instruction (ICAI) prototype system, particularly focusing on one component — the Speech Analyser. The speech analyser recognises a user’s speech, identifies the rhythmic stress pattern in the speech, discov-ers stress and rhythm errors in the speech, and provides reports for the other component generating personalised feedback to the user on ways of effectively improving the prosodic aspects of the speech. We build an Hidden Markov Model (HMM) based speech recogniser to recognise a user’s speech. A set of parameters for constructing the recogniser is investigated by an exhaustive experiment implemented in