Benjamin Fields

Capturing the workflows of music information retrieval for repeatability and reuse

Many solutions for the reuse and re-purposing of Music Information Retrieval (MIR) methods, and the tools implementing those methods, have been introduced over recent years. Proposals for achieving interoperability between systems have ranged from shared software libraries and interfaces, through common frameworks and portals, to standardised file formats and metadata. Here we assess these solutions for their suitability to be reused and combined as repurposable components within assemblies (or workflows) that can be used in novel and possibly more ambitious ways. Reuse and repeatability also have great implications for the process of MIR research: the encapsulation of any algorithm and its operation—including inputs, parameters, and outputs—is fundamental to the repeatability and reproducibility of an experiment. This is desirable both for the open and reliable evaluation of algorithms and for the advancement of MIR by building more effectively upon prior research. At present there is no clear best practice widely adopted by the field. Based upon our analysis of contemporary systems and their adoption we reflect as to whether this should be considered a failure. Are there limits to interoperability unique to MIR, and how might they be overcome? Beyond workflows how much research context can, and should, be captured? We frame our assessment within the emerging notion of Research Objects for reproducible research in other domains, and describe how their adoption could serve as a route to reuse in MIR.

Analysis and Exploitation of Musician Social Networks for Recommendation and Discovery

This paper presents an extensive analysis of a sample of a social network of musicians. The network sample is first analyzed using standard complex network techniques to verify that it has similar properties to other web-derived complex networks. Content-based pairwise dissimilarity values between the musical data associated with the network sample are computed, and the relationship between those content-based distances and distances from network theory explored. Following this exploration, hybrid graphs and distance measures are constructed, and used to examine the community structure of the artist network. Finally, results of these investigations are shown to be mostly orthogonal between these distance spaces. These results are considered with a focus recommendation and discovery applications employing these hybrid measures as their basis.

An e-Research approach to Web-scale music analysis

The growing quantity of digital recorded music available in large-scale resources such as the Internet archive provides an important new resource for musical analysis. An e-Research approach has been adopted in order to create a very substantive web-accessible corpus of musical analyses in a common framework for use by music scholars, students and beyond, and to establish a methodology and tooling that will enable others to add to the resource in the future. The enabling infrastructure brings together scientific workflow and Semantic Web technologies with a set of algorithms and tools for extracting features from recorded music. It has been used to deliver a prototype system, described here, that demonstrates the utility of Linked Data for enhancing the curation of collections of music signal data for analysis and publishing results that can be simply and readily correlated to these and other sources. This paper describes the motivation, infrastructure design and the proof-of-concept case study and reflects on emerging e-Research practice as researchers embrace the scale of the Web.

decibel 151

What happens if you become the search engine? If your participation creates the content? If by entering a space you become the entry?