Abstract
In this research a system for Arabic word segmentation into letters and recognition has been designed by dividing it into five groups (plosives, fricatives, nasals, glide and semi-vowel sounds) based on articulatory phonetics. This system include four main stages:
Stage one: Endpoint algorithm has been used to identify the beginning and the end of word.
Stage two: A new segmentation algorithm has been suggested and implemented depending upon time domain features and Arabic phonology rules.
Stage three: This stage includes letters feature extraction depending on linear predictive coding and system data base constructing which include vectors of features for the segmented letters from words and regarding letter recurring in different positions in the word.
Stage four: Includes Arabic letters recognition according to articulation which entails using Dynamic Time Warping (DTW) method that uses dynamic programming basics to obtain the matching path for the least distance accumulated value, where the word used in segmentation and recognition belongs to the four persons who create the data base and the results were in consistence which ranged from (75- 80)%
