Fundamental Frequency Estimation by
Least-Squares Harmonic Model Fitting
András Bánhalmi, Kornél Kovács,
András Kocsor, László Tóth
Research Group on Artificial Intelligence f the Hungarian
Academy of Sciences and University of Szeged, Hungary
This paper proposes a pitch estimation algorithm that is based on
optimal harmonic model fitting. The algorithm operates directly on the
time-domain signal and has a relatively simple mathematical background.
To increase its efficiency and accuracy, the algorithm is applied in
combination with an autocorrelation-based initialization phase. For
testing purposes we compare its performance on pitch-annotated corpora
with several conventional time-domain pitch estimation algorithms, and
also with a recently proposed one. The results show that even the autocorrelation-based
first phase significantly outperforms the traditional methods, and also
slightly the recently proposed yin algorithm. After applying
the second phase - the harmonic approximation step - the amount of errors
can be further reduced by about 20% relative to the error obtained in
the first phase.