Al-Quran recitation speech signals time series segmentation for speaker adaptation using dynamic time warping

Abstract

The transformation of the whole traditional process of Al-Quran Recitation into automated system application could raise the issues of robustness and integrity of recitation and correction quality and acceptance. There are several existing variations especially involve of rhythm, tone and length of recitation for different speaker. Dynamic Time warping (DTW) is used as dynamic programming to normalize the recitation speech length of speaker which warp the speech spectrum amplitude in time series for the experts and learners. DTW is used to gain the same length of recitation which warp the amplitudes, rhythm and tone into same length in time series segments based on formant frequency frame for different recitation speakers. There are 8 experts and 10 users from the Malay Muslim community had three selected surahs for Al-Quran recitation session. The aim of the paper is to normalize Al-Quran recitation speech signals as speaker adaption between experts and learner then represent each recitation speech signal at same vocal tract formant frequency that can be used in robust Automatic Recitation Recognition (ARR) to evaluate the performance of recitation evaluation.

Keywords: Al-Quran speech recitation, Automatic Recitation Recognition, speaker adaptation, vocal tract length normalization