DocumentCode
3295996
Title
Radon-based Audio Classification Features
Author
Gonzalez, Ruben
Author_Institution
Inst. for Integrated & Intell. Syst., Griffith Univ., Gold Coast, QLD, Australia
fYear
2012
fDate
9-13 July 2012
Firstpage
556
Lastpage
561
Abstract
This paper presents novel features for audio classification based on the Radon transform. These features are evaluated against widely accepted MFCC based features in terms of classification accuracy for a wide range of audio data sets.
Keywords
Radon transforms; audio signal processing; content-based retrieval; MFCC based features; Radon based audio classification features; Radon transform; audio data sets; content based retrieval; Error analysis; Feature extraction; Instruments; Mel frequency cepstral coefficient; Training; Transforms; Vectors; Audio classification; MFCC; Radon Transform; content-based retrieval; frog calls; indexing; insect sounds; k-NN classification; machine learning; musical instruments; spectral features; speech and music discrimination;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Expo (ICME), 2012 IEEE International Conference on
Conference_Location
Melbourne, VIC
ISSN
1945-7871
Print_ISBN
978-1-4673-1659-0
Type
conf
DOI
10.1109/ICME.2012.155
Filename
6298460
Link To Document