An Isolated Word Speaker Recognition System

Abstract

The paper presents a design of an isolated word speaker recognizer system by using the Hidden Markov Model. HTK toolkit is used as a design tool. The system is operated on a closed set of speakers and with a limited vocabulary of words. Digit utterances from one to ten with ten speakers (7 male, 3 female) are used as dataset in the system. It consists of isolated words that are separated by silences. Each speaker reads each word ten times. Six of them are used in training and the remaining are used in the test phase. The Mel cepstral coefficients are used in order to design the acoustic features and HMM models are constructed. A threshold calculation is performed for each speaker. After threshold adjustment, tests are performed for the performance evaluation and accuracy rates are calculated for each user. The system resulted in changing levels of recognition accuracy for each speaker and each word. © 2017 IEEE.