Feature extraction using fusion MFCC for continuous marathi speech recognition

Author

Gaikwad, Santosh ; Gawali, Bharti ; Yannawar, Pravin ; Mehrotra, Suresh

Author_Institution

Dept. of Comput. Sci. & Inf. Technol., Dr. Babasaheb Ambedkar Marathwada Univ., Aurangabad, India

fYear

2011

fDate

16-18 Dec. 2011

Firstpage

1

Lastpage

5

Abstract

This paper presents the performance of feature extraction techniques for speech recognition, for the classification of speech represented by a particular continuous sentence model. The goal of this study is to present independent as well as comparative performances of popular appearance based feature extraction techniques i.e. Linear Discriminative Analysed and Mel Frequency Cestrum Coefficient. Mel Frequency Cepstrum Coefficient (MFCC) helps us in extracting feature where as linear discriminant analysis (LDA) is used for reducing dimension of extracted feature. We experimented MFCC feature extraction individually and proposed a Fusion of MCCC and LDA for feature extraction.

Keywords

feature extraction; natural languages; signal classification; speech recognition; continuous Marathi speech recognition; continuous sentence model; feature extraction; fusion MFCC; linear discriminant analysis; mel frequency cepstrum coefficient; speech classification; Accuracy; Feature extraction; Linear discriminant analysis; Mel frequency cepstral coefficient; Speech; Speech recognition; Training; Fusion MFCC; LDA; MFCC; Speech Recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

India Conference (INDICON), 2011 Annual IEEE

Conference_Location

Hyderabad

Print_ISBN

978-1-4577-1110-7

Type

conf

DOI

10.1109/INDCON.2011.6139372

Filename

6139372