Harmonicity and dynamics-based features for audio
Features are very important for audio processing. Tasks like speech recognition and instrument identification are based on features. Most low-level features currently used are based on LPC and cepstral analysis. We propose a class of features based on dynamics and harmonicity. In particular, we define the notion of harmonic derivative. The efficacy of the features is demonstrated for music genre classification and instrument family classification. In particular, the features are shown to be cepstrum-equivalent.