A Novel Fundamental Frequency Estimator Based on Harmonic Pattern Match for Music Signals

The fundamental frequency (F0) is an ubiquitous and crucial feature of music signals. However, due to nonstationary noise, missing harmonics, nonideal, i.e., Undesired, physical vibration of the musical instruments, etc., the estimation of F0 represents a considerable challenge when desiring to obtain robust and reliable results. In this paper, a novel harmonic pattern match (HPM) algorithm for F0 estimation of music signals is proposed to achieve improved performance. The novel HPM algorithm relies on the autocorrelation both in the time domain and in the frequency domain, exploiting the spectrum subset to guide the searching of F0 candidates (FCs), and an efficient mechanism to evaluate the match between each FC and the harmonic pattern of the input signal. The harmonic pattern of the measured spectrum is converted into a set of sub-pitches, which are extracted from the segmented sub bands. Finally, the estimated F0 is selected to best match the sub-pitches under a weighting strategy. Validation experiments were carried out using a database representation of musical instruments consisting of single pitched notes and the viability of the HPM algorithm was demonstrated to be competitive with several other F0 estimators.