Experiments on ANN Based ASR Systems Using Limited Arabic Vocabulary

Abstract

In this paper we investigated Artificial Neural Networks (ANN) based Automatic Speech Recognition (ASR) by using limited Arabic vocabulary corpora. These limited Arabic vocabulary subsets are digits and vowels carried by specific carrier words. In addition to this, Hidden Markov Model (HMM) based ASR systems are designed and compared to ANN based systems by using the same corpora. All systems are isolated word speech recognizers. The ANN based recognition system achieved 99.5% correct digit recognition. On the other hand, the HMM based recognition system achieved 98.1% correct digit recognition. With vowels carrier words, the ANN based recognition system achieved 92.13% correct vowel recognition; but the HMM based recognition system achieved 91.6% correct vowel recognition.