A Manual System to Segment and Transcribe Arabic Speech

In this paper, we present our first work in the ¿computerized teaching of the Holly Quran¿ project, which aims to assist the memorization process of the Noble Quran based-on the speech recognition techniques. In order to build a high performance speech recognition system for this purpose, accurate acoustic models are essentials. Since annotated speech corpus of the Quranic sounds was not available yet, we tried to collect speech data from reciters memorizing the Quran and then focusing on their labeling and segmentation. It was necessarily, to propose a new labeling scheme which is able to cover all the Quranic Sounds and its phonological variations. In this paper, we present a set of labels that cover all the Arabic phonemes and their allophones and then show how it can be efficiently used to segment our Quranic corpus.