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\section{Introduction}  The abbreviation \textsc{skv} when applied to auditory signals was derived from \textbf{SK}ewness over \textbf{V}ariable time, reflecting the measure of asymmetry used (the \textit{Skewness} or \textit{third normalized moment}) and the technique of varying the time window over which this value was calculated. calculated \cite{Coath_2005}.  For image processing the \textbf{V} will stand for \textbf{V}ariable spatial frequency which also relates to the size of the window used. The \textsc{skv} algorithm was introduced as a method of identifying onsets and offsets in a model of auditory signal processing \cite{Coath_2005}. It is also an integral part of a model of auditory feature extraction \cite{Denham_2005} \cite{Coath_2007} and exhibits a range of desirable properties, as well as some features that make it biophysically plausible. The method has subsequently been used in a range of contexts including auditory salience detection \cite{Kovacs_2015}, beat tracking \cite{Coath_2009}, and studies of infant speech production \cite{Warlaumont_2016}.