We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Nonparametric estimation of the dynamic range of music signals.
- Authors
Coretto, Pietro; Giordano, Francesco
- Abstract
Summary: 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 of catching transient energy. This component is recovered by a simple rate‐optimal kernel estimator that requires a single data‐driven tuning parameter. 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 behaviour of the statistic is assessed based on a large numerical experiment where we simulate dynamic compression on a selection of real‐world 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.
- Subjects
DATA analysis; MUSIC data processing; NONPARAMETRIC estimation; REGRESSION analysis; STATISTICAL sampling
- Publication
Australian & New Zealand Journal of Statistics, 2017, Vol 59, Issue 4, p389
- ISSN
1369-1473
- Publication type
Article
- DOI
10.1111/anzs.12217