Beat space segmentation and octave scale cepstral feature for sung language recognition in pop music
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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The key or the scale information of a piece of music provides important clues on its high level musical content, like harmonic and melodic context, which can be useful for music classification, retrieval or further content analysis. Researchers have previously addressed the issue of finding the key for symbolically encoded music (MIDI); however, very little work has been done on key detection for acoustic music. In this paper, we present a method for estimating the root of diatonic scale and the key directly from acoustic signals (waveform) of popular and classical music. We propose a method to extract pitch profile features from the audio signal, which characterizes the tone distribution in the music. The diatonic scale root and key are estimated based on the extracted pitch profile by using a tone clustering algorithm and utilizing the tone structure of keys. Experiments on 72 music pieces have been conducted to evaluate the proposed techniques. The success rate of scale root detection for pop music pieces is above 90%.