Towards A Minimal Phonetic Set for Quran Recitation

Abstract

Speech is the most important interaction mechanism between human beings. Text-to-Speech synthesis problem has been addressed by many researchers in the literature for different languages. However, the Arabic language did not receive that much attention. This paper addresses a computational linguistic aspect in a phonetically transcribed syllabified Quranic text that is essential for developing speech synthesis prototype. The main objective of this work is to find a set of Quran verses (Ayat) that has the complete set of distinct syllables. An algorithm to find a reduced set for Quran verses that contains all Quran syllables is proposed. One of the motivations for this work is compressing the sound files of the Quran recitation. The current work proposes a technique to extract a reduced phonetic set of Quran recitation that can be used to develop Text-to-Speech system. It is found that out of 211,573 syllables – which Quran consists of – there are 2,642 distinct syllables that represents less than 1.25% of the Quranic syllables set. In addition, a reduced set of Quran verses that contains the whole set of distinct syllables is identified. The extracted set of verses represents around 16% of Quran verses.