Title :
A study of speech recognition system based on the Hidden Markov Model with Gaussian-Mixture
Author :
Ben Hazem, Zied ; Zouhir, Youssef ; Ouni, Kais
Author_Institution :
Higher Sch. of Technol. & Comput. Sci. (ESTI), Univ. of Carthage, Tunis, Tunisia
Abstract :
In this paper, we present a study of isolated word speech recognition system. The adopted system is based on the Hidden Markov Model with Gaussian Mixture (HMM-GM). We studied the recognition rate by varying the states number (3, 4, 5, 6 and 7 states) and the number of Gaussians per state (2, 4, 8, 12, 14 and 16 Gaussians) of Hidden Markov Model. We evaluated these recognition rates using two parameterization techniques Mel Frequency Cepstral Coefficients (MFCC) and Perceptual Linear Prediction (PLP). We have introduced the dynamic coefficients and the energy of the signal in order to achieve an improvement in the recognition rate.
Keywords :
Gaussian processes; hidden Markov models; mixture models; prediction theory; speech recognition; Gaussian-mixture model; HMM-GM model; MFCC; PLP; hidden Markov model; isolated word speech recognition system; mel frequency cepstral coefficient; parameterization technique; perceptual linear prediction; Automatic speech recognition; Hidden Markov models; Markov processes; Mel frequency cepstral coefficient; Reconnaissance; Speech;
Conference_Titel :
Electrical Sciences and Technologies in Maghreb (CISTEM), 2014 International Conference on
DOI :
10.1109/CISTEM.2014.7076916
