Further Studies of a FFT-Based Auditory Spectrum with Application in Audio Classification

摘要

In this paper,the noise-robustness of a recently proposed fast Fourier transform (FFT)-based auditory spectrum (FFT-AS) is further evaluated through speech/musicoise classification experiments wherein mismatched test cases are considered.The features obtained from the FFT-AS show more robust performance as compared to the conventional mel-frequency cepstral coefficient (MFCC) features.To further explore the FFT-AS from a perspective of practical audio classification,an audio classification algorithm using features derived from the FFT-AS is implemented on the floating-point DSP platform TMS320C6713.Through various optimization approaches,a significant reduction in the computational complexity is achieved wherein the implemented system demonstrates the ability to classify among speech,music and noise under the constraint of real-time processing.