Fundamental Frequency Estimation using Polynomial Rooting of a Subspace-Based Method

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Abstract

We consider the problem of estimating the fundamental frequency of periodic signals such as audio and speech. A novel estimation method based on polynomial rooting of the harmonic MUltiple SIgnal Classification (HMUSIC) is presented. By applying polynomial rooting, we obtain two significant improvements compared to HMUSIC. First, by using the proposed method we can obtain an estimate of the fundamental frequency without doing a grid search like in HMUSIC. This is due to that the fundamental frequency is estimated as the argument of the root lying closest to the unit circle. Second, we obtain a higher spectral resolution compared to HMUSIC which is a property of polynomial rooting methods. Our simulation results show that the proposed method is applicable to real-life signals, and that we in most cases obtain a higher spectral resolution than HMUSIC.
Original languageEnglish
JournalProceedings of the European Signal Processing Conference
Volume2010
Pages (from-to)502-506
ISSN2076-1465
Publication statusPublished - 2010

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Frequency estimation
Spectral resolution
Polynomials

Cite this

@inproceedings{d80d50cc0ad142cbbbd03d22f7343349,
title = "Fundamental Frequency Estimation using Polynomial Rooting of a Subspace-Based Method",
abstract = "We consider the problem of estimating the fundamental frequency of periodic signals such as audio and speech. A novel estimation method based on polynomial rooting of the harmonic MUltiple SIgnal Classification (HMUSIC) is presented. By applying polynomial rooting, we obtain two significant improvements compared to HMUSIC. First, by using the proposed method we can obtain an estimate of the fundamental frequency without doing a grid search like in HMUSIC. This is due to that the fundamental frequency is estimated as the argument of the root lying closest to the unit circle. Second, we obtain a higher spectral resolution compared to HMUSIC which is a property of polynomial rooting methods. Our simulation results show that the proposed method is applicable to real-life signals, and that we in most cases obtain a higher spectral resolution than HMUSIC.",
author = "Jensen, {Jesper Rindom} and Christensen, {Mads Gr{\ae}sb{\o}ll} and Jensen, {S{\o}ren Holdt}",
year = "2010",
language = "English",
volume = "2010",
pages = "502--506",
journal = "Proceedings of the European Signal Processing Conference",
issn = "2076-1465",
publisher = "European Association for Signal Processing (EURASIP)",

}

TY - GEN

T1 - Fundamental Frequency Estimation using Polynomial Rooting of a Subspace-Based Method

AU - Jensen, Jesper Rindom

AU - Christensen, Mads Græsbøll

AU - Jensen, Søren Holdt

PY - 2010

Y1 - 2010

N2 - We consider the problem of estimating the fundamental frequency of periodic signals such as audio and speech. A novel estimation method based on polynomial rooting of the harmonic MUltiple SIgnal Classification (HMUSIC) is presented. By applying polynomial rooting, we obtain two significant improvements compared to HMUSIC. First, by using the proposed method we can obtain an estimate of the fundamental frequency without doing a grid search like in HMUSIC. This is due to that the fundamental frequency is estimated as the argument of the root lying closest to the unit circle. Second, we obtain a higher spectral resolution compared to HMUSIC which is a property of polynomial rooting methods. Our simulation results show that the proposed method is applicable to real-life signals, and that we in most cases obtain a higher spectral resolution than HMUSIC.

AB - We consider the problem of estimating the fundamental frequency of periodic signals such as audio and speech. A novel estimation method based on polynomial rooting of the harmonic MUltiple SIgnal Classification (HMUSIC) is presented. By applying polynomial rooting, we obtain two significant improvements compared to HMUSIC. First, by using the proposed method we can obtain an estimate of the fundamental frequency without doing a grid search like in HMUSIC. This is due to that the fundamental frequency is estimated as the argument of the root lying closest to the unit circle. Second, we obtain a higher spectral resolution compared to HMUSIC which is a property of polynomial rooting methods. Our simulation results show that the proposed method is applicable to real-life signals, and that we in most cases obtain a higher spectral resolution than HMUSIC.

M3 - Conference article in Journal

VL - 2010

SP - 502

EP - 506

JO - Proceedings of the European Signal Processing Conference

JF - Proceedings of the European Signal Processing Conference

SN - 2076-1465

ER -