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Authors: Hussein Sharafeddin 1 ; Mageda Sharafeddin 2 and Haitham Akkary 2

Affiliations: 1 Lebanese University, Lebanon ; 2 American University of Beirut, Lebanon

Keyword(s): ALIZE, Biometric Authentication, LIA_RAL, Mobile Security, Speaker Verification, Text-independent Identification, Voice Recognition.

Related Ontology Subjects/Areas/Topics: Applications ; Audio and Speech Processing ; Biomedical Engineering ; Biomedical Signal Processing ; Biometrics ; Biometrics and Pattern Recognition ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Digital Signal Processing ; Health Engineering and Technology Applications ; Multimedia ; Multimedia Signal Processing ; Pattern Recognition ; Signal Processing ; Software Engineering ; Telecommunications

Abstract: The main contribution of this paper is providing an architecture for mobile users to authenticate user identity through short text phrases using robust open source voice recognition library ALIZE and speaker recognition tool LIA_RAL. Our architecture consists of a server connected to a group of subscribed mobile devices. The server is mainly needed for training the world model while user training and verification run on the individual mobile devices. The server uses a number of public random speaker text independent voice files to generate data, including the world model, used in training and calculating scores. The server data are shipped with the initial install of our package and with every subsequent package update to all subscribed mobile devices. For security purposes, training data consisting of raw voice and processed files of each user reside on the user’s device only. Verification is based on a short text-independent as well as text-dependent phrases, for ease of use and en hanced performance that gets processed and scored against the user trained model. While we implemented our voice verification in Android, the system will perform as efficiently in iOS. It will in fact be easier to implement since the base libraries are all written in C/C++. We show that the verification success rate of our system is 82%. Our system provides a free robust alternative to replace commercial voice identification and verification tools and extensible to implement more advanced mathematical models available in ALIZE and shown to improve voice recognition. (More)


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Paper citation in several formats:
Sharafeddin, H.; Sharafeddin, M. and Akkary, H. (2015). Voice Verification System for Mobile Devices based on ALIZE/LIA_RAL. In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM; ISBN 978-989-758-077-2; ISSN 2184-4313, SciTePress, pages 248-255. DOI: 10.5220/0005218902480255

author={Hussein Sharafeddin. and Mageda Sharafeddin. and Haitham Akkary.},
title={Voice Verification System for Mobile Devices based on ALIZE/LIA_RAL},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM},


JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM
TI - Voice Verification System for Mobile Devices based on ALIZE/LIA_RAL
SN - 978-989-758-077-2
IS - 2184-4313
AU - Sharafeddin, H.
AU - Sharafeddin, M.
AU - Akkary, H.
PY - 2015
SP - 248
EP - 255
DO - 10.5220/0005218902480255
PB - SciTePress