Traditional Machine Learning for Pitch Detection
TABLE IV: Overall accuracy of all pitch detectors.
['[EMPTY]', 'VDE', 'GPE', 'FPE', 'FFE']
We summarize now the overall pitch tracking performance along the 4 main objective metrics. For the proposed technique, we used either K-means,T or MLP for voicing detection, followed by the median filter for F0 estimation. Our proposed algorithm provides a significant reduction of the voicing errors, while maintaining state-of-art GPE and FPE capabilities. It is worth noticing that most pitch trackers avoid estimating F0 when unsure, which leads to better GPE and FPE but worse VDE. Overall, the proposed pitch detector yields a FFE of 3.8%, which is a 40% relative reduction over the best baseline (RAPT).