Automatic chord recognition from audio using a supervised HMM trained with audio-from-symbolic data


A novel approach for obtaining labeled training data is presented to directly estimate the model parameters in a supervised learning algorithm for automatic chord recognition from the raw audio. To this end, harmonic analysis is first performed on symbolic data to generate label files. In paral-lel, we synthesize audio data from the same symbolic data… (More)
DOI: 10.1145/1178723.1178726


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