DocumentCode
3459115
Title
A Mixed Parameter Method Based on MFCC and Fractal Dimension for Speech Recognition
Author
Yao, Minghai ; Hu, Jing ; Gu, Qinlong
Author_Institution
Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou
fYear
2006
fDate
20-23 Aug. 2006
Firstpage
1144
Lastpage
1146
Abstract
We propose a speech recognition approach with mixed parameter in this paper, which combines the traditional MFCC and fractal feature as the feature parameter. MFCC has higher spectrum resolution at low frequency segment, while it cannot represent speech nonlinearity. Fractal dimension is used to quantitatively describe the chaos nonlinearity in speech air flow. Experimental results demonstrate this method is promising in improving speech recognition performance.
Keywords
cepstral analysis; chaos; fractals; speech recognition; chaos nonlinearity; fractal dimension; fractal feature; mel-frequency cepstral coefficients; mixed parameter method; speech air flow; speech nonlinearity; speech recognition; Cepstral analysis; Chaos; Character recognition; Educational institutions; Fractals; Interpolation; Mel frequency cepstral coefficient; Power measurement; Speech recognition; Topology; Fractal Dimension; MFCC; Speech Recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Acquisition, 2006 IEEE International Conference on
Conference_Location
Shandong
Print_ISBN
1-4244-0528-9
Electronic_ISBN
1-4244-0529-7
Type
conf
DOI
10.1109/ICIA.2006.305906
Filename
4097839
Link To Document