Spoken Word Recognition Using Hidden Markov Model

Ramesh, P (2013) Spoken Word Recognition Using Hidden Markov Model. MTech thesis.



The main aim of this project is to develop isolated spoken word recognition system using Hidden Markov Model (HMM) with a good accuracy at all the possible frequency range of human voice. Here ten different words are recorded by different speakers including male and female and results are compared with different feature extraction methods. Earlier work includes recognition of seven small utterances using HMM with the use only one feature extraction method. This spoken word recognition system mainly divided into two major blocks. First includes recording data base and feature extraction of recorded signals. Here we use Mel frequency cepstral coefficients, linear cepstral coefficients and fundamental frequency as feature extraction methods. To obtain Mel frequency cepstral coefficients signal should go through the following: pre emphasis, framing, applying window function, Fast Fourier transform, filter bank and then discrete cosine transform, where as a linear frequency cepstral coefficients does not use Mel frequency. Second part describes HMM used for modeling and recognizing the spoken words. All the raining samples are clustered using K-means algorithm. Gaussian mixture containing mean, variance and weight are modeling parameters. Here Baum Welch algorithm is used for training the samples and re-estimate the parameters. Finally Viterbi algorithm recognizes best sequence that exactly matches for given sequence there is given spoken utterance to be recognized. Here all the simulations are done by the MATLAB tool and Microsoft window 7 operating system.

Item Type:Thesis (MTech)
Uncontrolled Keywords:Hidden Markov Model, MFCC,LFCC
Subjects:Engineering and Technology > Electronics and Communication Engineering > Optical Character Recognition
Divisions: Engineering and Technology > Department of Electronics and Communication Engineering
ID Code:5220
Deposited By:Hemanta Biswal
Deposited On:12 Dec 2013 14:04
Last Modified:12 Dec 2013 14:04
Supervisor(s):Ari, S

Repository Staff Only: item control page