A Computer Aided Pronunciation Learning system for teaching the holy quran Recitation rules

Abstract

This paper describes a speech-enabled Computer Aided Pronunciation Learning (CAPL) system. This system was developed for teaching Arabic pronunciations to non-native speakers. A challenging application of that system is teaching the correct recitation of the Holy Qur'an. This system uses a state of the art speech recognizer to detect errors in the user recitation. To increase accuracy of the speech recognizer, only probable pronunciation variants, that cover all common types of recitation errors, are examined by the speech decoder. A module for the automatic generation of pronunciation hypotheses is built as a component of the system. A phoneme duration classification algorithm is implemented to detect recitation errors related to phoneme durations. The decision reached by the recognizer is accompanied by a confidence score to reduce effect of misleading system feedbacks to unpredictable speech inputs. Assessment results for the performance of HAFSS system in three different countries are introduced.