Mining metadata from the web for AcousticBrainz

TitleMining metadata from the web for AcousticBrainz
Publication TypeConference Paper
Year of Publication2016
Conference Name3rd International Digital Libraries for Musicology workshop
AuthorsPorter, A., Bogdanov D., & Serra X.
AbstractSemantic annotations of music collections in digital libraries is important for organization and navigation of the content. These annotations and their associated metadata are useful in many Music Information Retrieval tasks, and related fields in musicology. Music collections used in research are growing in size, and therefore it is useful to use semiautomatic means to obtain such annotations. We present software tools for mining metadata from the web for the purpose of annotating music collections. These tools expand on data present in the AcousticBrainz database, which contains software-generated analysis of music audio files. Using this tool we gather metadata and semantic information from a variety of sources including both community-based services such as MusicBrainz, Last.fm, and Discogs, and commercial databases including Spotify, Itunes, and AllMusic. The tool can be easily expanded to start collecting data from a new source, and is automatically updated when new items are added to AcousticBrainz. We extract genre annotations for recordings in AcousticBrainz using our tool and study the agreement between folksonomies and expert sources. We discuss the results and explore possibilities for future work.
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