Arabic speech recognition using recurrent neural networks

Abstract

In this paper, a novel approach for implementing Arabic isolated speech recognition is described. While most of the literature on speech recognition (SR) is based on hidden Markov models (HMM), the present system is implemented by modular recurrent Elman neural networks (MRENN). The promising results obtained through this design show that this new neural networks approach can compete with the traditional HMM-based speech recognition approaches.