Sieve: a plugin for the automatic classification and intelligent browsing of kick and snare samples

The use of electronic drum samples is widespread in contemporary music productions, with music producers having an unprecedented number of samples available to them. To be efficient, users of these large collections require new tools to assist them in sorting, selection and auditioning tasks. This paper presents a new plugin for working with a large collection of kick and snare samples within a music production context. A database of 4230 kick and snare samples, representing 250 individual electronic drum machines are analyzed by segmenting the audio samples into different sample lengths and characterizing these segments using audio feature analysis. The resulting multidimensional feature space is reduced using principle component analysis (PCA). Samples are mapped to a 2D grid interface within an audio plug-in built using the JUCE software framework.