Arabic vowels characterization and classification using the normalized energy relating to formants and pitch

Vowels are the primary units of a sound system of a language. The classification of these vowels is therefore very important for the recognition and synthesis of speech. In this paper, we propose a normalized energy-based approach in formants and pitch to characterize Arabic vowels (short vowels: / a /, / i /, / u /; long vowels: / a: /, / i: /, / u: /). The classification was performed using a developed algorithm on records extracted from an Arabic corpus after the extraction of the pitch and the first three formants and the computation of the normalized energy in these bands. The results showed that the algorithm distinguishes Arabic vowels by analyzing the normalized energy in the nucleus of F1, F2, and F3 formants and pitch F0 with a rate of 88.7% for long vowels and a rate of 90% for short vowels