Title :
HMM Voice Recognition Algorithm Coding
Author :
Jarng, Soon Suck
Author_Institution :
Dept. of Control & Instrum., Chosun Univ., Gwang-Ju, South Korea
Abstract :
In this paper, the voice recognition algorithm based on HMM (Hidden Markov Modeling) is analyzed in detail. The HMM voice recognition algorithm is explained and the importance of voice information DB is revealed for better improvement of voice recognition rate. The feature vector of each voice characteristic parameter is chosen by means of MFCC (Mel Frequency Cepstral Coefficients). The extracting algorithm of syllable parts from continuous voice signal is introduced. This paper shows the relationship between recognition rates and number of applying syllables and number of groups for applying syllables.
Keywords :
codes; hidden Markov models; speech recognition; HMM voice recognition algorithm coding; Hidden Markov modeling; MFCC; Mel frequency cepstral coefficients; voice information; voice recognition rate; voice signal; Feature extraction; Hidden Markov models; Indexes; Mel frequency cepstral coefficient; Speech; Speech recognition; Training;
Conference_Titel :
Information Science and Applications (ICISA), 2011 International Conference on
Conference_Location :
Jeju Island
Print_ISBN :
978-1-4244-9222-0
Electronic_ISBN :
978-1-4244-9223-7
DOI :
10.1109/ICISA.2011.5772321