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TASLP
2008

A Noise-Robust FFT-Based Auditory Spectrum With Application in Audio Classification

8 years 10 months ago
A Noise-Robust FFT-Based Auditory Spectrum With Application in Audio Classification
In this paper, we investigate the noise robustness of Wang and Shamma's early auditory (EA) model for the calculation of an auditory spectrum in audio classification applications. First, a stochastic analysis is conducted wherein an approximate expression of the auditory spectrum is derived to justify the noise-suppression property of the EA model. Second, we present an efficient fast Fourier transform (FFT)-based implementation for the calculation of a noise-robust auditory spectrum, which allows flexibility in the extraction of audio features. To evaluate the performance of the proposed FFT-based auditory spectrum, a set of speech/ music/noise classification tasks is carried out wherein a support vector machine (SVM) algorithm and a decision tree learning algorithm (C4.5) are used as the classifiers. Features used for classification include conventional Mel-frequency cepstral coefficients (MFCCs), MFCC-like features obtained from the original auditory spectrum (i.e., based on th...
Wei Chu, B. Champagne
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TASLP
Authors Wei Chu, B. Champagne
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