Alfredo Esquivel Jaramillo — accepted AI-conference papers

2020

Robust Fundamental Frequency Estimation in Coloured Noise

Alfredo Esquivel Jaramillo, Andreas Jakobsson, Jesper Kjær Nielsen, Mads Græsbøll Christensen

ICASSP 2020accepted

Most parametric fundamental frequency estimators make the implicit assumption that any corrupting noise is additive, white Gaus-sian. Under this assumption, the maximum likelihood (ML) and the least squares estimators are the same, and statistically efficient. However, in the coloured noise case, th…

Cited by 5 Source ↗Scholar ↗

2019

A Study on How Pre-whitening Influences Fundamental Frequency Estimation

Alfredo Esquivel Jaramillo, Jesper Kjær Nielsen, Mads Græsbøll Christensen

ICASSP 2019accepted

This paper deals with the influence of pre-whitening for the task of fundamental frequency estimation in noisy conditions. Parametric fundamental frequency estimators commonly assume that the noise is white and Gaussian and, therefore, they are only statistically efficient under those conditions. Th…

Cited by 0 Source ↗Scholar ↗