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Wireless Communications and Mobile Computing
Volume 2018, Article ID 1013234, 12 pages
Research Article

A Novel Technique for Speech Recognition and Visualization Based Mobile Application to Support Two-Way Communication between Deaf-Mute and Normal Peoples

1Department of Software Engineering, University of Engineering and Technology, Taxila 47050, Pakistan
2College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
3College of Computer and Information Systems, Al-Yamamah University, Riyadh 11512, Saudi Arabia
4Department of Computer Engineering, Umm Al-Qura University, Makkah 21421, Saudi Arabia
5Department of Mathematics, University of Engineering and Technology, Taxila 47050, Pakistan
6Department of Statistics and Finance, University of Science and Technology of China, Hefei 23026, China

Correspondence should be addressed to Kanwal Yousaf; kp.ude.alixatteu@fasuoy.lawnak

Received 15 January 2018; Accepted 17 April 2018; Published 24 May 2018

Academic Editor: Seyed M. Buhari

Copyright © 2018 Kanwal Yousaf et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Mobile technology is very fast growing and incredible, yet there are not much technology development and improvement for Deaf-mute peoples. Existing mobile applications use sign language as the only option for communication with them. Before our article, no such application (app) that uses the disrupted speech of Deaf-mutes for the purpose of social connectivity exists in the mobile market. The proposed application, named as vocalizer to mute (V2M), uses automatic speech recognition (ASR) methodology to recognize the speech of Deaf-mute and convert it into a recognizable form of speech for a normal person. In this work mel frequency cepstral coefficients (MFCC) based features are extracted for each training and testing sample of Deaf-mute speech. The hidden Markov model toolkit (HTK) is used for the process of speech recognition. The application is also integrated with a 3D avatar for providing visualization support. The avatar is responsible for performing the sign language on behalf of a person with no awareness of Deaf-mute culture. The prototype application was piloted in social welfare institute for Deaf-mute children. Participants were 15 children aged between 7 and 13 years. The experimental results show the accuracy of the proposed application as 97.9%. The quantitative and qualitative analysis of results also revealed that face-to-face socialization of Deaf-mute is improved by the intervention of mobile technology. The participants also suggested that the proposed mobile application can act as a voice for them and they can socialize with friends and family by using this app.