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/music/noise 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.

作者: Wei Chu Beno(i)t Champagne

作者单位: Department of Electrical and Computer EngineeringMcGill University,Montréal,Québec,Canada Department of Electrical and Computer Engineering McGill University,Montréal,Québec,Canada

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）