13,113 research outputs found
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
Instrumentational complexity of music genres and why simplicity sells
Listening habits are strongly influenced by two opposing aspects, the desire
for variety and the demand for uniformity in music. In this work we quantify
these two notions in terms of musical instrumentation and production
technologies that are typically involved in crafting popular music. We assign a
"complexity value" to each music style. A style is complex if it shows the
property of having both high variety and low uniformity in instrumentation. We
find a strong inverse relation between variety and uniformity of music styles
that is remarkably stable over the last half century. Individual styles,
however, show dramatic changes in their "complexity" during that period. Styles
like "new wave" or "disco" quickly climbed towards higher complexity in the 70s
and fell back to low complexity levels shortly afterwards, whereas styles like
"folk rock" remained at constant high complexity levels. We show that changes
in the complexity of a style are related to its number of sales and to the
number of artists contributing to that style. As a style attracts a growing
number of artists, its instrumentational variety usually increases. At the same
time the instrumentational uniformity of a style decreases, i.e. a unique
stylistic and increasingly complex expression pattern emerges. In contrast,
album sales of a given style typically increase with decreasing complexity.
This can be interpreted as music becoming increasingly formulaic once
commercial or mainstream success sets in.Comment: 17 pages, 5 figures, Supporting Informatio
Connected Learning Journeys in Music Production Education
The field of music production education is a challenging one, exploring multiple creative, technical and entrepreneurial disciplines, including music composition, performance electronics, acoustics, musicology, project management and psychology. As a result, students take multiple âlearning journeysâ on their pathway towards becoming autonomous learners. This paper uniquely evaluates the journey of climbing Bloomâs cognitive domain in the field of music production and gives specific examples that validate teaching music production in higher education through multiple, connected ascents of the framework. Owing to the practical nature of music production, Kolbâs Experiential Learning Model is also considered as a recurring function that is necessary for climbing Bloomâs domain, in order to ensure that learners are equipped for employability and entrepreneurship on graduation. The authorsâ own experiences of higher education course delivery, design and development are also reflected upon with reference to Music Production pathways at both the University of Westminster (London, UK) and York St John University (York, UK)
Genreanalyse und Film : eine Arbeitsbibliographie
Die Bibliographie listet Artikel zur allgemeinen Problematik der Genres in Filmtheorie und -geschichte auf. Dabei werden auch einige allgemeine poetologische Arbeiten zum Generischen aufgefĂŒhrt. Studien zu einzelnen Genres sind nur dann aufgefĂŒhrt, wenn sie von allgemeinerem Interesse sind. FĂŒr Hinweise danke ich Ludger Kaczmarek, Angela Keppler und Jörg Schweinitz
Automatic Genre Classification of Latin Music Using Ensemble of Classifiers
This paper presents a novel approach to the task of automatic music genre classification which is based on ensemble learning. Feature vectors are extracted from three 30-second music segments from the beginning, middle and end of each music piece. Individual classifiers are trained to account for each music segment. During classification, the output provided by each classifier is combined with the aim of improving music genre classification accuracy. Experiments carried out on a dataset containing 600 music samples from two Latin genres (Tango and Salsa) have shown that for the task of automatic music genre classification, the features extracted from the middle and end music segments provide better results than using the beginning music segment. Furthermore, the proposed ensemble method provides better accuracy than using single classifiers and any individual segment
On the genre-fication of Music: a percolation approach (long version)
In this paper, we analyze web-downloaded data on people sharing their music
library. By attributing to each music group usual music genres (Rock, Pop...),
and analysing correlations between music groups of different genres with
percolation-idea based methods, we probe the reality of these subdivisions and
construct a music genre cartography, with a tree representation. We also show
the diversity of music genres with Shannon entropy arguments, and discuss an
alternative objective way to classify music, that is based on the complex
structure of the groups audience. Finally, a link is drawn with the theory of
hidden variables in complex networks.Comment: 7 pages, 5 figures, submitted to the proceedings of the 3rd
International Conference NEXT-SigmaPh
Uncovering collective listening habits and music genres in bipartite networks
In this paper, we analyze web-downloaded data on people sharing their music
library, that we use as their individual musical signatures (IMS). The system
is represented by a bipartite network, nodes being the music groups and the
listeners. Music groups audience size behaves like a power law, but the
individual music library size is an exponential with deviations at small
values. In order to extract structures from the network, we focus on
correlation matrices, that we filter by removing the least correlated links.
This percolation idea-based method reveals the emergence of social communities
and music genres, that are visualised by a branching representation. Evidence
of collective listening habits that do not fit the neat usual genres defined by
the music industry indicates an alternative way of classifying listeners/music
groups. The structure of the network is also studied by a more refined method,
based upon a random walk exploration of its properties. Finally, a personal
identification - community imitation model (PICI) for growing bipartite
networks is outlined, following Potts ingredients. Simulation results do
reproduce quite well the empirical data.Comment: submitted to PR
Performance recordivity : studio music in a live context
A broad range of positions is articulated in the academic literature around the relationship between recordings and live performance. Auslander (2008) argues that âlive performance ceased long ago to be the primary experience of popular music, with the result that most live performances of popular music now seek to replicate the music on the recordingâ. Elliott (1995) suggests that âhit songs are often conceived and produced as unambiguous and meticulously recorded performances that their originators often duplicate exactly in live performancesâ. Wurtzler (1992) argues that âas socially and historically produced, the categories of the live and the recorded are defined in a mutually exclusive relationship, in that the notion of the live is premised on the absence of recording and the defining fact of the recorded is the absence of the liveâ. Yet many artists perform in ways that fundamentally challenge such positions. Whilst it is common practice for musicians across many musical genres to compose and construct their musical works in the studio such that the recording is, in Auslanderâs words, the âoriginal performanceâ, the live version is not simply an attempt to replicate the recorded version. Indeed in some cases, such replication is impossible. There are well known historical examples. Queen, for example, never performed the a cappella sections of Bohemian Rhapsody because it they were too complex to perform live. A 1966 recording of the Beach Boys studio creation Good Vibrations shows them struggling through the song prior to its release. This paper argues that as technology develops, the lines between the recording studio and live performance change and become more blurred. New models for performance emerge. In a 2010 live performance given by Grammy Award winning artist Imogen Heap in New York, the artist undertakes a live, improvised construction of a piece as a performative act. She invites the audience to choose the key for the track and proceeds to layer up the various parts in front of the audience as a live performance act. Her recording process is thus revealed on stage in real time and she performs a process that what would have once been confined to the recording studio. So how do artists bring studio production processes into the live context? What aspects of studio production are now performable and what consistent models can be identified amongst the various approaches now seen? This paper will present an overview of approaches to performative realisations of studio produced tracks and will illuminate some emerging relationships between recorded music and performance across a range of contexts
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