This paper is concerned with the results of complex approach to statistical properties of various music signals, based on 412 musical pieces classified in 12 different genres. Analysed signals contain more than 24 hours of music. For each piece time variation of the signal level was found, performed with a 10 ms period of integration in rms calculation and with 90% overlap, making a new signal representing the level as a function of time. For each piece the statistical analysis of signal level has been performed by its statistical distribution, cumulative distribution, effective value within complete duration of piece, mean level value, and level value corresponding to maximum of the statistical distribution. The parameter L1, L10, L50 and L99 were extracted from cumulative distributions as numerical indicators of dynamic properties. The paper contains detailed statistical data and averaged data for all observed genres, as well as quantitative data about dynamic range and crest factor of various music signals.
https://www.aes.org/e-lib/browse.cfm?elib=14898
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