FMA: A Dataset For Music Analysis

We introduce the Free Music Archive (FMA), an open and easily accessible dataset suitable for evaluating several tasks in MIR, a field concerned with browsing, searching, and organizing large music collections. The community's growing interest in feature and end-to-end learning is however restrained by the limited availability of large audio datasets. The FMA aims to overcome this hurdle by providing 917 GiB and 343 days of Creative Commons-licensed audio from 106,574 tracks from 16,341 artists and 14,854 albums, arranged in a hierarchical taxonomy of 161 genres. It provides full-length and high-quality audio, pre-computed features, together with track- and user-level metadata, tags, and free-form text such as biographies. We here describe the dataset and how it was created, propose a train/validation/test split and three subsets, discuss some suitable MIR tasks, and evaluate some baselines for genre recognition. Code, data, and usage examples are available at https://github.com/mdeff/fmaComment: ISMIR 2017 camera-read

The Topology of Music Recommendation Networks

We study the topology of several music recommendation networks, which rise from relationships between artist, co-occurrence of songs in playlists or experts' recommendation. The analysis uncovers the emergence of complex network phenomena in this kind of recommendation networks, built considering artists as nodes and their resemblance as links. We observe structural properties that provide some hints on navigation and possible optimizations on the design of music recommendation systems. Finally, the analysis derived from existing music knowledge sources provides a deeper understanding of the human music similarity perceptions.Comment: 15 pages, 3 figure

Download, Stream, or Somewhere in Between: The Potential for Legal Music Use in Podcasting

Podcasting is an increasingly popular new digital technology with the potential to be a great conduit of expression. Currently, the use of music is limited in podcasting due in large part to uncertainty as to what rights must be licensed before copyrighted music can be used legitimately. This iBrief examines what legal rights are implicated by podcasting by analyzing U.S. copyright law and comparing related technologies. This iBrief concludes that onerous licensing requirements are unnecessary, and for podcasting to realize its potential, a simple licensing framework must be established

Comparison of popular music in the United States and the United Kingdom: computerized analysis of 42,714 pieces

The present research employed computerised analyses of all those pieces to have achieved any degree of commercial success in either the United States or the United Kingdom in terms of energy, beats per minutes, and several emotion scores. Analyses showed differences between these two commercially-complete musical cultures in all variables except one of the emotion scores; that the relationship between popularity and each of the remaining variables was similar across the two countries; but that there were differences in the representation of genres. These findings indicate that it is possible to identify quantitative differences between musical cultures, and may have implications for ethnomusicology and the nascent digital music streaming industry

Language Ideologies, Choices, and Practices in Eastern African Hip Hop

Hip hop emerged as a musical and cultural force during the late 1970s in the United States and has followed a global trajectory ever since. Artists and fans around the world filter North American hip hop styles through their own local musical, social, and linguistic environments, making hip hop a highly visible (and audible) example of the intersection of global and local youth cultures. Young people in Tanzania and Malawi, neighboring African countries in the eastern region of the continent, are no exception to this creative process. Both countries have vibrant hip hop communities that draw on youth knowledge of international, as well as local and national, hip hop music and culture. Youth in the two countries listen to the same popular American stars and hold similar ideas about and interpretations of their lives and music. Yet, Tanzanian and Malawian hip hop scenes diverge in the social and cultural significance of local musical practices, which include performing as well as dancing, dressing, and talking about rap music. This tension between the similar and the different serves as an analytic backdrop for what follows

Folks in Folksonomies: Social Link Prediction from Shared Metadata

Web 2.0 applications have attracted a considerable amount of attention because their open-ended nature allows users to create light-weight semantic scaffolding to organize and share content. To date, the interplay of the social and semantic components of social media has been only partially explored. Here we focus on Flickr and Last.fm, two social media systems in which we can relate the tagging activity of the users with an explicit representation of their social network. We show that a substantial level of local lexical and topical alignment is observable among users who lie close to each other in the social network. We introduce a null model that preserves user activity while removing local correlations, allowing us to disentangle the actual local alignment between users from statistical effects due to the assortative mixing of user activity and centrality in the social network. This analysis suggests that users with similar topical interests are more likely to be friends, and therefore semantic similarity measures among users based solely on their annotation metadata should be predictive of social links. We test this hypothesis on the Last.fm data set, confirming that the social network constructed from semantic similarity captures actual friendship more accurately than Last.fm's suggestions based on listening patterns.Comment: http://portal.acm.org/citation.cfm?doid=1718487.171852