Automatic Chord Recognition from Audio Using Enhanced Pitch Class Profile
نویسنده
چکیده
In this paper, a feature vector called the Enhanced Pitch Class Profile (EPCP) is introduced for automatic chord recognition from the raw audio. To this end, the Harmonic Product Spectrum is first obtained from the DFT of the input signal, and then an algorithm for computing a 12-dimensional pitch class profile is applied to it to give the EPCP feature vector. The EPCP vector is correlated with the pre-defined templates for 24 major/minor triads, and the template yielding maximum correlation is identified as the chord of the input signal. The experimental results show the EPCP yields less errors than the conventional PCP in frame-rate chord recognition.
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