In this paper, hidden Markov modeling technique is applied to Arabic speech recognition. In addition, vector quantization process of speech data is performed based on auditory modeling procedure. The work introduces the first results achieved in the initial development of an isolated-word recognizer based on vector quantization and hidden Markov models for Arabic and its application to limited vocabulary represented by the ten Arabic digits. The proposed speech recognizer is designed to operate in real time on an IBM PC whose performance is enhanced by the IBM signal processor.