Differential Qiraat Processing Applications using Spectrogram Voice Analysis

This study provides a review of efforts made so far to develop applications that assist in proper Quranic recitation based on the spectrogram voice analysis. The voice recorded from users’ recitation is used to compare with the sample recitation features collected from expert reciters that have been stored in the database. These comparison is utilized to evaluate the performance result of the various algorithms that have been applied in Quranic recitation processing. Before reviewing how to develop the actual applications, a study was made to determine the effectiveness of spectrogram voice analysis. Samples are often collected to measure the articulation of Arabic letters. The collected samples are analyzed using Fourier analysis technique. The sound features samples’ waveforms are transformed into spectrums that are basically frequency representations of the signals. The spectrogram is used to determine the formant frequency and are observed for each subject to determine its mean formant frequency. Subsequently after features extraction, a classification algorithm is employed to compare the features extracted in real-time with that available in the knowledge base. Based on the results obtained, the processes are often developed into mobile applications for portability.