Research on Intelligent Robot Command-Word Recognition System Based on Feature Extraction

Author

Zhang, Yi ; Li, Yanhua ; Zeng, Li ; Liu, Quanjie

Author_Institution

Res. Center of Intell. Syst. & Robot., Chongqing Univ. of Posts & Telecommun., Chongqing, China

fYear

2009

fDate

4-6 Nov. 2009

Firstpage

1

Lastpage

4

Abstract

According to the problem of the low recognition rate of speaker-independent recognition in intelligent robot, a kind of endpoint detection algorithm with double threshold is adopted and the speech endpoint can be detected accurately. The mixed parameter of Mel frequency cepstral coefficients (MFCC) and fractal dimension is used as the feature parameter, and the intelligent robot command-word recognition system based on hidden Markov models (HMM) is realized. The recognition effect achieves above 85%. Then the performance of MFCC and the mixed parameter of MFCC and fractal dimension is contrasted and analyzed. The experiment result shows that the system recognition rate is improved by the algorithm of mixed parameter, and the system recognition performance is optimized.

Keywords

feature extraction; hidden Markov models; intelligent robots; speech recognition; Mel frequency cepstral coefficients; double threshold; endpoint detection algorithm; feature extraction; fractal dimension; hidden Markov models; intelligent robot command-word recognition system; speaker-independent recognition; speech endpoint detection; Cepstral analysis; Detection algorithms; Feature extraction; Fractals; Hidden Markov models; Intelligent robots; Intelligent systems; Mel frequency cepstral coefficient; Speech recognition; Zinc;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2009. CCPR 2009. Chinese Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-4199-0

Type

conf

DOI

10.1109/CCPR.2009.5344015

Filename

5344015