Physical Models for Fast Estimation of Guitar String, Fret and Plucking Position

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

21 Downloads (Pure)

Resumé

In this paper, a novel method for analyzing guitar performances is proposed. It is both fast and effective at extracting the activated string, fret, and plucking position from guitar recordings. The method is derived from guitar-string physics and, unlike the state of the art, does not require audio recordings as training data. A maximum a posteriori classifier is proposed for estimating the string and fret based on a simulated model of feature vectors while the plucking position is estimated using estimated inharmonic partials. The method extracts features from audio with a pitch estimator that estimates also the inharmonicity of the string. The string and fret classifier is evaluated on recordings of an electric and acoustic guitar under noisy conditions. The performance is comparable to the state of the art, and the performance is shown to degrade at SNRs below 20 dB. The plucking position estimator is evaluated in a proof-of-concept experiment with sudden changes of string, fret and plucking positions, which shows that these can be estimated accurately. The proposed method operates on individual 40 ms segments and is thus suitable for high-tempo and real-time applications.
OriginalsprogEngelsk
TitelIEEE Workshop on Applications of Signal Processing to Audio and Acoustics
Antal sider5
Udgivelses stedNew Paltz, NY
StatusAccepteret/In press - 2019

Fingerprint

Classifiers
Audio recordings
Physics
Acoustics
Experiments

Citer dette

Hjerrild, J. M., Willemsen, S., & Christensen, M. G. (Accepteret/In press). Physical Models for Fast Estimation of Guitar String, Fret and Plucking Position. I IEEE Workshop on Applications of Signal Processing to Audio and Acoustics New Paltz, NY.
@inproceedings{f7f3f774a8524cfabf9c76f0f08265d2,
title = "Physical Models for Fast Estimation of Guitar String, Fret and Plucking Position",
abstract = "In this paper, a novel method for analyzing guitar performances is proposed. It is both fast and effective at extracting the activated string, fret, and plucking position from guitar recordings. The method is derived from guitar-string physics and, unlike the state of the art, does not require audio recordings as training data. A maximum a posteriori classifier is proposed for estimating the string and fret based on a simulated model of feature vectors while the plucking position is estimated using estimated inharmonic partials. The method extracts features from audio with a pitch estimator that estimates also the inharmonicity of the string. The string and fret classifier is evaluated on recordings of an electric and acoustic guitar under noisy conditions. The performance is comparable to the state of the art, and the performance is shown to degrade at SNRs below 20 dB. The plucking position estimator is evaluated in a proof-of-concept experiment with sudden changes of string, fret and plucking positions, which shows that these can be estimated accurately. The proposed method operates on individual 40 ms segments and is thus suitable for high-tempo and real-time applications.",
keywords = "physical modelling, statistical signal processing, parametric pitch estimation, Music information retrieval",
author = "Hjerrild, {Jacob M{\o}ller} and Silvin Willemsen and Christensen, {Mads Gr{\ae}sb{\o}ll}",
year = "2019",
language = "English",
booktitle = "IEEE Workshop on Applications of Signal Processing to Audio and Acoustics",

}

Hjerrild, JM, Willemsen, S & Christensen, MG 2019, Physical Models for Fast Estimation of Guitar String, Fret and Plucking Position. i IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. New Paltz, NY.

Physical Models for Fast Estimation of Guitar String, Fret and Plucking Position. / Hjerrild, Jacob Møller; Willemsen, Silvin; Christensen, Mads Græsbøll.

IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. New Paltz, NY, 2019.

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

TY - GEN

T1 - Physical Models for Fast Estimation of Guitar String, Fret and Plucking Position

AU - Hjerrild, Jacob Møller

AU - Willemsen, Silvin

AU - Christensen, Mads Græsbøll

PY - 2019

Y1 - 2019

N2 - In this paper, a novel method for analyzing guitar performances is proposed. It is both fast and effective at extracting the activated string, fret, and plucking position from guitar recordings. The method is derived from guitar-string physics and, unlike the state of the art, does not require audio recordings as training data. A maximum a posteriori classifier is proposed for estimating the string and fret based on a simulated model of feature vectors while the plucking position is estimated using estimated inharmonic partials. The method extracts features from audio with a pitch estimator that estimates also the inharmonicity of the string. The string and fret classifier is evaluated on recordings of an electric and acoustic guitar under noisy conditions. The performance is comparable to the state of the art, and the performance is shown to degrade at SNRs below 20 dB. The plucking position estimator is evaluated in a proof-of-concept experiment with sudden changes of string, fret and plucking positions, which shows that these can be estimated accurately. The proposed method operates on individual 40 ms segments and is thus suitable for high-tempo and real-time applications.

AB - In this paper, a novel method for analyzing guitar performances is proposed. It is both fast and effective at extracting the activated string, fret, and plucking position from guitar recordings. The method is derived from guitar-string physics and, unlike the state of the art, does not require audio recordings as training data. A maximum a posteriori classifier is proposed for estimating the string and fret based on a simulated model of feature vectors while the plucking position is estimated using estimated inharmonic partials. The method extracts features from audio with a pitch estimator that estimates also the inharmonicity of the string. The string and fret classifier is evaluated on recordings of an electric and acoustic guitar under noisy conditions. The performance is comparable to the state of the art, and the performance is shown to degrade at SNRs below 20 dB. The plucking position estimator is evaluated in a proof-of-concept experiment with sudden changes of string, fret and plucking positions, which shows that these can be estimated accurately. The proposed method operates on individual 40 ms segments and is thus suitable for high-tempo and real-time applications.

KW - physical modelling

KW - statistical signal processing

KW - parametric pitch estimation

KW - Music information retrieval

M3 - Article in proceeding

BT - IEEE Workshop on Applications of Signal Processing to Audio and Acoustics

CY - New Paltz, NY

ER -

Hjerrild JM, Willemsen S, Christensen MG. Physical Models for Fast Estimation of Guitar String, Fret and Plucking Position. I IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. New Paltz, NY. 2019