Analysis of patterns in speaker authentication using discrete probability HMMs

The advances in computer hardware combined with innovative artificial intelligence (AI) techniques can be a powerful methodology to perform intelligent cognitive tasks. We have investigated speech recognition techniques using hidden Markov models and successfully classified speakers based on their utterances. This paper proposes a discrete probability HMMS based approach to successfully classify speakers based on their utterances. The results show that we have got high accuracy in identifying the speakers. This leads us to conclude that uncertain reasoning and learning are vital components of AI that could lead to the development of automated intelligent solutions to various complex and interesting problems.