In the present paper, the phonological feature geometry of the Persian phonemes is analyzed in the form of articulate-free and articulate-bound features based on the articulator model of the nonlinear phonology. Then, the reference phonetic pattern of each feature that consists of one or a set of acoustic correlates, characterized by the quantitative or qualitative values in its phonological representation, is determined by the acoustic and statistical analysis of the collected data. Finally, an algorithm is designed which implements multiple modules based on the identified acoustic correlates of the phonological features and gets as input an acoustic signal of a Persian phoneme in CV or VC context and outputs the recognized phoneme. The findings of the paper can considerably improve the speed and accuracy of the Persian speech recognition systems.