Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.071204
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 12, 2016.
Abstract: Text to Speech (TTS) Conversion Systems have been an area of research for decades and have been developed for both handwritten and typed text in various languages. Existing research shows that it has been a challenging task to deal with Urdu language due to the complexity of Urdu ‘Nastaliq’ (rich variety in writing styles), therefore, to the best of our knowledge, not much work has been carried out in this area. Keeping in view the importance of Urdu language and the lack of development in this domain, our research focuses on ‘handwritten’ Urdu TTS system. The idea is to first recognize a handwritten Urdu character and then convert it into an audible human speech. Since handwriting styles of different people vary greatly from each other, a machine learning technique for the recognition part is used i.e., Artificial Neural Networks (ANN). Correctly recognized characters, then, undergo processing which converts them into human speech. Using this methodology, a working prototype has been successfully implemented in MATLAB that gives an overall accuracy of 91.4%. Our design serves as a platform for further research and future enhancements for word and sentence processing, especially for visually impaired people.
Tajwar Sultana, Abdul Rehman Abbasi, Bilal Ahmed Usmani, Sadeem Khan, Wajeeha Ahmed, Naima Qaseem and Sidra, “Towards Development of Real-Time Handwritten Urdu Character to Speech Conversion System for Visually Impaired” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071204