Digital Music Lab: A Framework for Analysing Big Music Data

• Main Authors: Abdallah, S, Benetos, E, Gold, NE, Hargreaves, S, Weyde, T, Wolff, D
• Format: Report
• Language: English
• Published: IEEE 2016
• Subjects: Feature extraction; Metadata; Histograms; Data mining; Libraries; Audio recording; Servers; DML
• Online Access: https://discovery.ucl.ac.uk/id/eprint/1505744/1/1570255859-3.pdf; https://discovery.ucl.ac.uk/id/eprint/1505744/

In the transition from traditional to digital musicology, large scale music data are increasingly becoming available which require research methods that work on the collection level and at scale. In the Digital Music Lab (DML) project, a software system has been developed that provides large-scale analysis of music audio with an interactive interface. The DML system includes distributed processing of audio and other music data, remote analysis of copyright-restricted data, logical inference on the extracted information and metadata, and visual web-based interfaces for exploring and querying music collections. A system prototype has been set up in collaboration with the British Library and I Like Music Ltd, which has been used to analyse a diverse corpus of over 250,000 music recordings. In this paper we describe the system requirements, architecture, components, and data sources, explaining their interaction. Use cases and applications with initial evaluations of the proposed system are also reported.