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In this paper we describe an approach to identify the name of a piece ofpiano music, based on a short audio excerpt of a performance. Given only adescription of the pieces in text format (i.e. no score information isprovided), a reference database is automatically compiled by acquiring a numberof audio representations (performances of the pieces) from internet sources.These are transcribed, preprocessed, and used to build a reference database viaa robust symbolic fingerprinting algorithm, which in turn is used to identifynew, incoming queries. The main challenge is the amount of noise that isintroduced into the identification process by the music transcription algorithmand the automatic (but possibly suboptimal) choice of performances to representa piece in the reference database. In a number of experiments we show how toimprove the identification performance by increasing redundancy in thereference database and by using a preprocessing step to rate the referenceperformances regarding their suitability as a representation of the pieces inquestion. As the results show this approach leads to a robust system that isable to identify piano music with high accuracy -- without any need for dataannotation or manual data preparation.

Piece Identification in Classical Piano Music Without Reference Scores