Creative professional users musical relevance criteria

Although known item searching for music can be dealt with by searching metadata using existing text search techniques, human subjectivity and variability within the music itself make it very difficult to search for unknown items. This paper examines these problems within the context of text retrieval and music information retrieval. The focus is on ascertaining a relationship between music relevance criteria and those relating to relevance judgements in text retrieval. A data-rich collection of relevance judgements by creative professionals searching for unknown musical items to accompany moving images using real world queries is analysed. The participants in our observations are found to take a socio-cognitive approach and use a range of content and context based criteria. These criteria correlate strongly with those arising from previous text retrieval studies despite the many differences between music and text in their actual content

Changing Practice in a National Legal Deposit Library

This two-part essay considers how digital culture has influenced ideas about permanence and looks at the change in collecting practice in a legal deposit library. The author asks: how is the idea of permanence, understood in cultural heritage terms, influencing digital culture and thus digital technology? The first part of the essay touches upon the concepts associated with permanence, digital culture, digital technology, social change, and cultural institutions, in relation to collecting digital cultural material. The second part of this essay focuses on the change in collecting practice of the Alexander Turnbull Library (Turnbull Library) at the National Library of New Zealand in developing its heritage collection of electronically published material with the benefit of legal deposit, with a particular focus on the change in practice to include the collection of online publications

Music 2025 : The Music Data Dilemma: issues facing the music industry in improving data management

© Crown Copyright 2019Music 2025ʼ investigates the infrastructure issues around the management of digital data in an increasingly stream driven industry. The findings are the culmination of over 50 interviews with high profile music industry representatives across the sector and reflects key issues as well as areas of consensus and contrasting views. The findings reveal whilst there are great examples of data initiatives across the value chain, there are opportunities to improve efficiency and interoperability

Crowdsourcing Emotions in Music Domain

An important source of intelligence for music emotion recognition today comes from user-provided community tags about songs or artists. Recent crowdsourcing approaches such as harvesting social tags, design of collaborative games and web services or the use of Mechanical Turk, are becoming popular in the literature. They provide a cheap, quick and efficient method, contrary to professional labeling of songs which is expensive and does not scale for creating large datasets. In this paper we discuss the viability of various crowdsourcing instruments providing examples from research works. We also share our own experience, illustrating the steps we followed using tags collected from Last.fm for the creation of two music mood datasets which are rendered public. While processing affect tags of Last.fm, we observed that they tend to be biased towards positive emotions; the resulting dataset thus contain more positive songs than negative ones