Template-Based Vibrato Analysis of Music Signals
This is the accompanying website for the paper "Template-Based Vibrato Analysis of Music Signals".
Abstract
The automated analysis of vibrato in complex music signals is a highly challenging task. A common strategy is to proceed in a two-step fashion. First, a fundamental frequency (F0) trajectory for the musical voice that is likely to exhibit vibrato is estimated. In a second step, the trajectory is then analyzed with respect to periodic frequency modulations. As a major drawback, however, such a method cannot recover from errors made in the inherently difficult first step, which severely limits the performance during the second step. In this work, we present a novel vibrato analysis approach that avoids the first error-prone F0-estimation step. Our core idea is to perform the analysis directly on a signal's spectrogram representation where vibrato is evident in the form of characteristic spectro-temporal patterns. We detect and parameterize these patterns by locally comparing the spectrogram with a predefined set of vibrato templates. Our systematic experiments indicate that this approach is more robust than F0-based strategies.
Dataset
All audio files and annotations used in our paper: [.zip]
3.1 Evaluation: Vibrato Detection
Here you find all results of our vibrato detection experiment from Section 3.1.
Sound On Sound Demo - Mystery
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Giselle - You
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Leaf - Full
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Phre The Eon - Everybody is Falling Apart
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Secretariat - Borderline
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Sunshine Garcia Band - For I Am The Moon
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Angela Thomas Wade - Milk Cow Blues
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Triviul - Dorothy
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Funny Valentines - Sleigh Ride
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3.2 Evaluation: Vibrato Analysis
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