A Novel Approach to Spoken Arabic Number Recognition Based on Developed Ant Lion Algorithm

Abstract

Intelligent spoken system is constructed to recognize numbers spoken in Arabic language by different people. Series of operations are performed on audio sound file as pre-processing stages. A novel approach is applied to extract features of audio files called Max Mean Log to reduce audio file dimensions in an efficient manner. Several stages of initial processing are used to prepare the file for the next step of the recognition process. The recognition process begins with the use of Antlion’s advanced intelligence algorithm to determine the type of the spoken number in Arabic and later convert it to a visual text that represents the value of the spoken number. The current proposal method is relatively fast and very effective. The percentage of recognizing numbers spoken by the proposed algorithm is 99%. For 1,800 different audio files, the error rate was 1%. Additional 40 audio files were used that are different from people’s original dataset. Due to an additional examination of the system and its ability to recognize the audio file, the rate of discrimination for such files was 72.5%.