@InProceedings{6952551,
  author = {S. Karimian-Azari and J. R. Jensen and M. G. Christensen},
  booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
  title = {Robust pitch estimation using an optimal filter on frequency estimates},
  year = {2014},
  pages = {1557-1561},
  abstract = {In many scenarios, a periodic signal of interest is often contaminated by different types of noise, that may render many existing pitch estimation methods suboptimal, e.g., due to an incorrect white Gaussian noise assumption. In this paper, a method is established to estimate the pitch of such signals from unconstrained frequency estimates (UFEs). A minimum variance distortionless response (MVDR) method is proposed as an optimal solution to minimize the variance of UFEs considering the constraint of integer harmonics. The MVDR filter is designed based on noise statistics making it robust against different noise situations. The simulation results confirm that the proposed MVDR method outperforms the state-of-the-art weighted least squares (WLS) pitch estimator in colored noise and has robust pitch estimates against missing harmonics in some time-frames.},
  keywords = {filtering theory;frequency estimation;least squares approximations;robust pitch estimation;optimal filter;frequency estimates;suboptimal pitch estimation method;incorrect white Gaussian noise assumption;signal pitch estimation;unconstrained frequency estimates;minimum variance distortionless response method;MVDR method;UFE variance minimization;integer harmonics;MVDR filter;noise statistics;weighted least square pitch estimator;WLS pitch estimator;colored noise;Harmonic analysis;Frequency estimation;Maximum likelihood estimation;Gaussian noise;Colored noise;Audio signal;harmonic model;pitch estimation;minimum variance distortionless response (MVDR);maximum likelihood (ML)},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925075.pdf},
}

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In this paper, a method is established to estimate the pitch of such signals from unconstrained frequency estimates (UFEs). A minimum variance distortionless response (MVDR) method is proposed as an optimal solution to minimize the variance of UFEs considering the constraint of integer harmonics. The MVDR filter is designed based on noise statistics making it robust against different noise situations. The simulation results confirm that the proposed MVDR method outperforms the state-of-the-art weighted least squares (WLS) pitch estimator in colored noise and has robust pitch estimates against missing harmonics in some time-frames.","keywords":"filtering theory;frequency estimation;least squares approximations;robust pitch estimation;optimal filter;frequency estimates;suboptimal pitch estimation method;incorrect white Gaussian noise assumption;signal pitch estimation;unconstrained frequency estimates;minimum variance distortionless response method;MVDR method;UFE variance minimization;integer harmonics;MVDR filter;noise statistics;weighted least square pitch estimator;WLS pitch estimator;colored noise;Harmonic analysis;Frequency estimation;Maximum likelihood estimation;Gaussian noise;Colored noise;Audio signal;harmonic model;pitch estimation;minimum variance distortionless response (MVDR);maximum likelihood (ML)","issn":"2076-1465","month":"Sep.","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925075.pdf","bibtex":"@InProceedings{6952551,\n author = {S. Karimian-Azari and J. R. Jensen and M. G. Christensen},\n booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},\n title = {Robust pitch estimation using an optimal filter on frequency estimates},\n year = {2014},\n pages = {1557-1561},\n abstract = {In many scenarios, a periodic signal of interest is often contaminated by different types of noise, that may render many existing pitch estimation methods suboptimal, e.g., due to an incorrect white Gaussian noise assumption. In this paper, a method is established to estimate the pitch of such signals from unconstrained frequency estimates (UFEs). A minimum variance distortionless response (MVDR) method is proposed as an optimal solution to minimize the variance of UFEs considering the constraint of integer harmonics. The MVDR filter is designed based on noise statistics making it robust against different noise situations. 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