A Study on how Pre-whitening Influences Fundamental Frequency Estimation

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Resumé

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. The noise is coloured in many practical applications and this will often result in problems of misidentifying an integer divisor or multiple of the true fundamental frequency (i.e., octave errors). The purpose of this paper is to see if pre-whitening can reduce this problem, based on noise statistics obtained from existing noise PSD estimation algorithms. For this purpose, different noise types and prediction orders of LPC pre-whitening are considered. The results show that pre-whitening improves the estimation accuracy of an NLS pitch estimator significantly when the noise is fairly stationary. For nonstationary noise, the improvements are modest at best, but we hypothesize that this is due to the noise PSD estimation performance rather than the LPC pre-whitening principle.
OriginalsprogEngelsk
TitelIEEE International Conference on Acoustics, Speech and Signal Processing
Publikationsdato2019
StatusAccepteret/In press - 2019

Fingeraftryk

Frequency estimation
Gaussian noise (electronic)
White noise
Statistics

Emneord

    Citer dette

    Esquivel Jaramillo, A., Nielsen, J. K., & Christensen, M. G. (Accepteret/In press). A Study on how Pre-whitening Influences Fundamental Frequency Estimation. I IEEE International Conference on Acoustics, Speech and Signal Processing
    @inproceedings{d9deeff61dbf46fba714f88a13d3e62a,
    title = "A Study on how Pre-whitening Influences Fundamental Frequency Estimation",
    abstract = "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. The noise is coloured in many practical applications and this will often result in problems of misidentifying an integer divisor or multiple of the true fundamental frequency (i.e., octave errors). The purpose of this paper is to see if pre-whitening can reduce this problem, based on noise statistics obtained from existing noise PSD estimation algorithms. For this purpose, different noise types and prediction orders of LPC pre-whitening are considered. The results show that pre-whitening improves the estimation accuracy of an NLS pitch estimator significantly when the noise is fairly stationary. For nonstationary noise, the improvements are modest at best, but we hypothesize that this is due to the noise PSD estimation performance rather than the LPC pre-whitening principle.",
    keywords = "fundamental frequency, pre-whitening, spectral flatness measure, gross error rate",
    author = "{Esquivel Jaramillo}, Alfredo and Nielsen, {Jesper Kj{\ae}r} and Christensen, {Mads Gr{\ae}sb{\o}ll}",
    year = "2019",
    language = "English",
    booktitle = "IEEE International Conference on Acoustics, Speech and Signal Processing",

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    Esquivel Jaramillo, A, Nielsen, JK & Christensen, MG 2019, A Study on how Pre-whitening Influences Fundamental Frequency Estimation. i IEEE International Conference on Acoustics, Speech and Signal Processing.

    A Study on how Pre-whitening Influences Fundamental Frequency Estimation. / Esquivel Jaramillo, Alfredo; Nielsen, Jesper Kjær; Christensen, Mads Græsbøll.

    IEEE International Conference on Acoustics, Speech and Signal Processing. 2019.

    Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

    TY - GEN

    T1 - A Study on how Pre-whitening Influences Fundamental Frequency Estimation

    AU - Esquivel Jaramillo, Alfredo

    AU - Nielsen, Jesper Kjær

    AU - Christensen, Mads Græsbøll

    PY - 2019

    Y1 - 2019

    N2 - 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. The noise is coloured in many practical applications and this will often result in problems of misidentifying an integer divisor or multiple of the true fundamental frequency (i.e., octave errors). The purpose of this paper is to see if pre-whitening can reduce this problem, based on noise statistics obtained from existing noise PSD estimation algorithms. For this purpose, different noise types and prediction orders of LPC pre-whitening are considered. The results show that pre-whitening improves the estimation accuracy of an NLS pitch estimator significantly when the noise is fairly stationary. For nonstationary noise, the improvements are modest at best, but we hypothesize that this is due to the noise PSD estimation performance rather than the LPC pre-whitening principle.

    AB - 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. The noise is coloured in many practical applications and this will often result in problems of misidentifying an integer divisor or multiple of the true fundamental frequency (i.e., octave errors). The purpose of this paper is to see if pre-whitening can reduce this problem, based on noise statistics obtained from existing noise PSD estimation algorithms. For this purpose, different noise types and prediction orders of LPC pre-whitening are considered. The results show that pre-whitening improves the estimation accuracy of an NLS pitch estimator significantly when the noise is fairly stationary. For nonstationary noise, the improvements are modest at best, but we hypothesize that this is due to the noise PSD estimation performance rather than the LPC pre-whitening principle.

    KW - fundamental frequency

    KW - pre-whitening

    KW - spectral flatness measure

    KW - gross error rate

    M3 - Article in proceeding

    BT - IEEE International Conference on Acoustics, Speech and Signal Processing

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    Esquivel Jaramillo A, Nielsen JK, Christensen MG. A Study on how Pre-whitening Influences Fundamental Frequency Estimation. I IEEE International Conference on Acoustics, Speech and Signal Processing. 2019