An investigation into several pitch detection algorithms for singing phrases analysis

Abstract

This article provides an investigation into four different pitch detection algorithms: pYin, Praat, Phase Lock Loops (PLL)-based, and an Extended Complex Kalman Filter approach. The first two algorithms compute the pitch on a frame-by-frame basis while the latter two work on a sample-by-sample basis. Only in recent years has there been a noticeable increase in the number of papers applying pitch detection techniques to sung phrases. This investigation is done on a dataset contained 76 files of singers. To create a ground truth from the data an alternative approach using the Spear analysis program is applied. The algorithms are compared using a new Singing Data Analyser tool. It was observed that the pYin and Praat are the most reliable algorithms while the PLL and Kalman filter algorithms are very dependent on the user-selected parameters.