Using natural language input and audio analysis for a human-oriented MIR system

We present a MIR (music information retrieval) system using natural language as input for human-oriented queries to large-scale music collections. The outlined system is a full-fledged architecture combining state-of-the-art approaches from the fields of natural language and the automatic analysis of audio data. Our approach copes with meta tag construction, content-based classification of audio and uses music ontologies as a backbone for the representation of musical knowledge. On top of this architecture different prototypes for industrial applications are described including first results of real-life field tests. This work has been performed at the German Research Center for AI and the authors spin-off company, the Sonicson GmbH.