  There has been a rapid growth of digitally available music data, including
audio recordings, digitized images of sheet music, album covers and liner
notes, and video clips. This huge amount of data calls for retrieval strategies
that allow users to explore large music collections in a convenient way. More
precisely, there is a need for cross-modal retrieval algorithms that, given a
query in one modality (e.g., a short audio excerpt), find corresponding
information and entities in other modalities (e.g., the name of the piece and
the sheet music). This goes beyond exact audio identification and subsequent
retrieval of metainformation as performed by commercial applications like
Shazam [1].
