Human Voice Authentication System using Hidden Marcov Model

Speaker authentication is the process of automatically identifying before who is talking on the base of person information included in speech waves. Many principles are used in the area of voice recognition. This paper provides a method of storing the voiceprints of individuals uniquely, based on the Hidden Markov Model. HMM has been used in the speech recognition area for a long period of time, but this project explores a way of using HMM for voice authentication which is different from speech recognition. This voiceprint will then be used for voice authentication, using text independent speaker recognition methods in which the system does not have belief in on special wording being talked, but one and only on the voice of the speaker. This paper also provides details about certain misconceptions with regard to voice authentication that exist in the society. This paper explains more about the user training phase detailing how the voice print of an individual is stored in the system by extracting certain properties of the waveform using HMM.