This article describes an off-line handwritten Arabic words recognition system. Both explicit grapheme segmen- tation and feature extraction are originally designed for Latin cursive handwriting. The recognizer itself is a Hybrid HMM/NN. We introduce a new shape-based alphabet for handwriting Arabic recognition which is intended to benefit from some specificities of Arabic writing. We performed several experiments using IFN/ENIT benchmark database to validate our approach. Our rec- ognizer performs as close as the state of the art recogni- tion rate with 87%. The latter results are indeed very en- couraging as many perspectives and improvements may be considered. Especially, the explicit processing of dots and diacritics, therefore making use of more prior knowledge of Arabic writing specificities.