# Correct Pronunciation Detection of the Arabic Alphabet Using Deep Learning
## 5 Conclusions  
In this paper, we have proposed a framework for CA speech recognition using deep learning techniques including DCNN, AlexNet, and BLSTM. We implemented these learning models and demonstrated their results on the Arabic alphabet audio dataset. Several experiments are performed using three different validation techniques including random splitting, 5-fold cross-validation, and hold-out validation. AlexNet outperformed the DCNN and BLSTM in the classification tasks. We have performed two tasks, i.e., Arabic alphabet classification and Arabic alphabet pronunciation classification using augmented and non-augmented dataset while we have achieved promising results with data augmentation.  
The first part of this research is Arabic alphabet classification, which is successfully performed by using AlexNet and yielded an accuracy of 98.41% with data augmentation.  
Figure 9: Comparison of DCNN, AlexNet, and BLSTM models with and without data augmentation using different validation strategies. (**a**) Alphabet classification. (**b**) Pronunciation classification.  
The second part of this research is the Arabic alphabet pronunciation classification using the AlexNet model and, we achieved an accuracy of 99.14% with data augmentation. As future work, we would like to extend the proposed method to incorporate more feature sets and increase the size of the dataset for words and sentence recognition. We would further like to investigate some new network architectures, i.e., Xception, Inception, ResNet, and NASNet.  
Conceptualization, H.F.A. and K.R.; methodology, N.Z., H.F.A., K.R., I.F., M.Z. and A.A.; software, N.Z.; validation, N.Z.; formal analysis, N.Z., K.R., and I.F.; resources, H.F.A.; data curation, N.Z. and H.F.A.; writing--original draft preparation, N.Z.; writing--review and editing, H.F.A., K.R., I.F., M.Z. and A.A.; visualization, N.Z. and K.R. All authors have read and agreed to the published version of the manuscript.  
Deanship of Scientific Research, King Faisal University, Saudi Arabia.  
The study has been performed as per the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards and approved by Institutional Review Board (or Ethics Committee) of Qaudi-I-Azam University Islamabad, Pakistan (7 July 2020).  
Informed Consent Statement: Informed consent was obtained from the guardians of minor participants and all the individual participants included in this research work while collecting the audio dataset.  
The wav data format is used to support the findings of this study. The dataset is collected from very few online resources: 1. [[http://www.Arabicquick.com/learn_Arabic_alphabet/](http://www.Arabicquick.com/learn_Arabic_alphabet/)]([http://www.Arabicquick.com/learn_Arabic_alphabet/](http://www.Arabicquick.com/learn_Arabic_alphabet/)) (accessed on 4 April 2019); 2. [[https://languagehub.co.nz/reading-writing-arabic-alphabet-audio-downloads/](https://languagehub.co.nz/reading-writing-arabic-alphabet-audio-downloads/)]([https://languagehub.co.nz/reading-writing-arabic-alphabet-audio-downloads/](https://languagehub.co.nz/reading-writing-arabic-alphabet-audio-downloads/)) (accessed on 28 March 2019); 3. [[https://www.searchtruth.com/quran/teacher/1/](https://www.searchtruth.com/quran/teacher/1/)]([https://www.searchtruth.com/quran/teacher/1/](https://www.searchtruth.com/quran/teacher/1/)) (accessed on 4 April 2019). Due to the limited availability of the audio data regarding our research, we have collected our own dataset with the help of [PERSON] and [PERSON]. Dataset available at: [[https://drive.google.com/drive/folders/1](https://drive.google.com/drive/folders/1) GXyFO6 LGBgo-FNRjDlu5]([https://drive.google.com/drive/folders/1](https://drive.google.com/drive/folders/1) GXyFO6 LGBgo-FNRjDlu5) fRALkoAb2 en2 (accessed on 4 April 2019).  
This work is supported by the Deanship of Scientific Research, King Faisal University, Al-Ahsa, Saudi Arabia.  
The authors declare no conflict of interest.