Quality assessment on muscle locations for speech representation

There are more than 68 muscles, which are activated either simultaneously or sequentially during speech production. To monitor the signals from all these muscles at once, involve a lot of sensors and such system is very expensive. In the Quran therapeutic treatment applications, the use of specific muscles is very important, for the production of correct Arabic pronunciation. The proper pronunciation will improve the reader's understanding of what is being read, thus assisting the effectiveness of the therapy process. The objective of this study is to identify the most optimal muscle location, which is suitable for monitoring the quality of a recitation during the Quran’s therapeutic process, based on the information content embedded in their Electromyogram (EMG) signals. Empirical Mode Decomposition (EMD) technique was used in this study to extract features of the EMG while the combination of Hilbert Huang Spectral Entropy (HHSE) and Kullback Leibler Divergence (KLD) techniques were used to quantify the information content in each feature. Combination of these techniques managed to rank ten widely used speech muscles in the literature based upon their information content. Four muscle locations have been suggested, which is believed to be sufficient in developing a low-cost self-assessment system for monitoring Quran recitation.