A very low latency pitch tracker for audio to midi conversion
Résumé
An algorithm for estimating the fundamental frequency of a single-pitch audio signal is described, for application to audio-to-MIDI conversion. In order to minimize latency, this method is based on the ESPRIT algorithm, together with a statistical model for partials frequencies. It is tested on real guitar recordings and compared to the YIN estimator. We show that, in this particular context, both methods exhibit a similar accuracy but the periodicity measure, used for note segmentation, is much more stable with the ESPRIT-based algorithm. This allows to significantly reduce ghost notes. This method is also able to get very close to the theoretical mini-mum latency, i.e. the fundamental period of the lowest observable pitch. Furthermore, it appears that fast implementations can reach a reasonable complexity and could be compatible with real-time, although this is not tested is this study.
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