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arXiv · 1312.0538

Nonparametric estimation of the dynamic range of music signals

Pietro Coretto·Francesco Giordano
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Abstract

The dynamic range is an important parameter which measures the spread of sound power, and for music signals it is a measure of recording quality. There are various descriptive measures of sound power, none of which has strong statistical foundations. We start from a nonparametric model for sound waves where an additive stochastic term has the role to catch transient energy. This component is recovered by a simple rate-optimal kernel estimator that requires a single data-driven tuning. The distribution of its variance is approximated by a consistent random subsampling method that is able to cope with the massive size of the typical dataset. Based on the latter, we propose a statistic, and an estimation method that is able to represent the dynamic range concept consistently. The behavior of the statistic is assessed based on a large numerical experiment where we simulate dynamic compression on a selection of real music signals. Application of the method to real data also shows how the proposed method can predict subjective experts' opinions about the hifi quality of a recording.

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Pietro Coretto, Francesco Giordano. 2018-02-14. Nonparametric estimation of the dynamic range of music signals. https://doi.org/10.1111/anzs.12217

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