Social Cognition and Melodic Persistence: Where Metadata and Content Diverge
نویسنده
چکیده
The automatic retrieval of members of a tune family from a database of melodies is potentially complicated by well documented divergences between textual metadata and musical content. We examine recently reported cases of such divergences in search of musical features which persist even when titles change or the melodies themselves vary. We find that apart from meter and mode, the rate of preservation of searchable musical features is low. Social and gestural factors appear to play a varying role in establishing the “melodic” identity of widely transmitted songs. The rapid growth of social computing bring urgency to better understanding the different ways in which “same” or “similar” can be defined.
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تاریخ انتشار 2006