Distance metrics and indexing strategies for a digital library of popular music

People identify powerfully with music: someone might say “that´s my song!” but they are unlikely to say “that´s my book!” or “that´s my picture!” A digital library of popular music therefore has the potential to be a compelling application of information retrieval technology. Such a library requires a retrieval method that is appropriate for a non-technical audience. Experiments on “query by humming”, which attempt to retrieve a tune based on sampled recording of a user singing an excerpt, have heretofore concentrated on relatively small, well-curated collections. Scaling up introduces three problems: availability of source material, an increase in false positive hits, and slower retrieval. We describe our experiments with MIDI files, propose a new, more accurate distance metric between queries and songs, and discuss possibilities for efficient indexing