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Audio content fingerprinting based on two-dimensional constant Q-factor transform representation and robust audio identification for time-aligned applications
Audio content fingerprinting based on two-dimensional constant Q-factor transform representation and robust audio identification for time-aligned applications
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机译：基于二维恒定Q因子变换表示的音频内容指纹识别和针对时间对齐应用的可靠音频识别
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摘要
Content identification methods for consumer devices determine robust audio fingerprints that are resilient to audio distortions. One method generates signatures representing audio content based on a constant Q-factor transform (CQT). A 2D spectral representation of a 1D audio signal facilitates generation of region based signatures within frequency octaves and across the entire 2D signal representation. Also, points of interest are detected within the 2D audio signal representation and interest regions are determined around selected points of interest. Another method generates audio descriptors using an accumulating filter function on bands of the audio spectrum and generates audio transform coefficients. A response of each spectral band is computed and transform coefficients are determined by filtering, by accumulating derivatives with different lags, and computing second order derivatives. Additionally, time and frequency based onset detection determines audio descriptors at events and enhances descriptors with information related to an event.
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