The WITCHCRAFT project sets as its objective to develop a fully functional content-based retrieval system for folk song melodies. Besides making the Netherlands folk song collection of the Meertens Institute available for the general public, we aim to support their research in oral variation. Folk song researchers traditionally know many songs by heart and intuitively find correlations between them. For large or international collections, however, researchers cannot know all the song instances, so computer-aided support is indispensable to reveal related items. In principle this means to take existing models about oral variation in designing and implementing similarity measures that can be used in a retrieval system. This, however, proves to be difficult in practice. In this paper we present our information retrieval setup consisting of performed folk song recordings, their symbolic encoding, an expert classification of variant tunes (ground truth), annotation data about the particular expert classification reasons and our approaches to similarity. As an example we present how we translated the expert concept of "pitch stability" into an alignment-based similarity measure and how we evaluated our method and the original "pitch stability" hypothesis with respect to the given annotations.
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