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When instrumentalists perform with vibrato, they add a quasi-periodic frequency modulation to the note. Although this modulation is rarely purely sinusoidal, many methods for vibrato parameterization focus exclusively on the rate and depth of the frequency modulation, with less attention given to measuring how a performer’s vibrato changes over the course of a note. In this paper we interpret the vibrato trajectories as instantiations of a random process that can be characterized by an associated autocorrelation function and power spectral density. From these distributions, a coherence time can be estimated that describes the stability of the vibrato within a note. This metric can be used to characterize individual performers as well as for resynthesizing vibratos of different styles.
Author (s): Smith, Sarah R.;
Bocko, Mark F.;
Affiliation:
University of Rochester, Rochester, NY, USA
(See document for exact affiliation information.)
AES Convention: 145
Paper Number:10069
Publication Date:
2018-10-06
Session subject:
Acoustics and Signal Processing
DOI:
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Smith, Sarah R.; Bocko, Mark F.; 2018; A Statistical Metric for Stability in Instrumental Vibrato [PDF]; University of Rochester, Rochester, NY, USA; Paper 10069; Available from: https://aes.org/publications/elibrary-page/?id=19795
Smith, Sarah R.; Bocko, Mark F.; A Statistical Metric for Stability in Instrumental Vibrato [PDF]; University of Rochester, Rochester, NY, USA; Paper 10069; 2018 Available: https://aes.org/publications/elibrary-page/?id=19795
@inproceedings{Smith2018a,
title={{A Statistical Metric for Stability in Instrumental Vibrato}},
author={Smith, Sarah R. and Bocko, Mark F.},
year={2018},
month={oct},
booktitle={Journal of the Audio Engineering Society},
publisher={Paper 10069; AES Convention 145; October 2018},
number={10069},
organization={AES},
}
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