LAUSR

With the increasing number and popularity of smart devices in the past few decades, especially those that execute different types of health-related applications, their security is a growing concern. Biometric authentication can be used for device security, and speaker recognition (SR) is one of its elegant forms. In this study, an SR system is developed for the security of smart devices, which identifies a person from the shortest utterance of Arabic language, achieving the highest SR rate, by using the benchmark Linguistic Data Consortium (LDC) Arabic dataset. This study focuses on the use of the consonants and vowels of the Arabic language. It is observed that certain consonants or a fusion of certain consonants in Arabic language helps to ascertain the speaker’s identity efficiently. The shortest utterance that better presents the speaker’s identity by using such consonants is revealed. The system was analyzed by using different numbers of consonants and achieved the maximum (100%) SR rate using a fusion of only three consonants of the Arabic language. These consonants or their combinations can be used to develop text for any speaker-based authentication system.