Showing papers by "J. Stephen Downie published in 2011"

Design and creation of a large-scale database of structural annotations

Abstract: This paper describes the design and creation of an unprecedentedly large database of over 2400 structural annotations of nearly 1400 musical recordings. The database is intended to be a test set for algorithms that will be used to analyze a much larger corpus of hundreds of thousands of recordings, as part of the Structural Analysis of Large Amounts of Musical Information (SALAMI) project. This paper describes the design goals of the database and the practical issues that were encountered during its creation. In particular, we discuss the selection of the recordings, the development of an annotation format and procedure that adapts work by Peeters and Deruty [10], and the management and execution of the project. We also summarize some of the properties of the resulting corpus of annotations, including average inter-annotator agreement.

Music structure segmentation algorithm evaluation: expanding on mirex 2010 analyses and datasets

Abstract: Music audio structure segmentation has been a task in the Music Information Retrieval Evaluation eXchange (MIREX) since 2009. In 2010, five algorithms were evaluated against two datasets (297 and 100 songs) with an almost exclusive focus on western popular music. A new annotated dataset significantly larger in size and with a more diverse range of musical styles became available in 2011. This new dataset comprises over 1,300 songs spanning pop, jazz, classical, and world music styles. The algorithms from the 2010 iteration of MIREX are re-evaluated against this new dataset. This paper presents a detailed analysis of these evaluation results in order to gain a better understanding of the current state-of-the-art in automatic structure segmentation. These expanded analyses focus on the interaction of algorithm performance and rankings with datasets, musical styles, and annotation level. Because the new dataset contains multiple annotations for each song, we also introduce a baseline for expected human performance for this task.

An e-Research approach to Web-scale music analysis

Abstract: 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.

Exploiting music structures for digital libraries

Abstract: This demonstration presents a music structure-based audio/visual interface for the navigation of very large scale music digital libraries. This work is a product of the Structural Analysis of Large Amounts of Music Information (SALAMI) project.