Title :
Text-Independent Speaker Identification Using Hidden Markov Models
Author :
Deshpande, Mangesh S. ; Holambe, Raghunath S.
Author_Institution :
SRES Coll. of Eng., Kopargaon
Abstract :
This paper presents a closed-set, text-independent speaker identification using continuous density hidden Markov model (CDHMM). Each registered speaker has a separate HMM which is trained using Baum-Welch algorithm. The system performance has been studied for different system parameters such as the number of states, number of mixture components per state and the amount of data required for training. Identification accuracy of 100% is achieved by conducting the experiments on TIMIT database.
Keywords :
hidden Markov models; speaker recognition; Baum-Welch algorithm; CDHMM; TIMIT database; continuous density hidden Markov model; hidden Markov models; text-independent speaker identification; Concatenated codes; Databases; Educational institutions; Hidden Markov models; Probability density function; Speaker recognition; Speech; Strontium; System performance; Vector quantization; Speaker identification; admissible wavelet packet tree; hidden Markov model;
Conference_Titel :
Emerging Trends in Engineering and Technology, 2008. ICETET '08. First International Conference on
Conference_Location :
Nagpur, Maharashtra
Print_ISBN :
978-0-7695-3267-7
Electronic_ISBN :
978-0-7695-3267-7
DOI :
10.1109/ICETET.2008.46
