scispace - formally typeset
Search or ask a question
Proceedings Article

A taxonomy of musical genres

12 Apr 2000-pp 1238-1245
TL;DR: This work describes a novel music genre taxonomy based on a few guiding principles, and reports on the process of building this taxonomy.
Abstract: The recent progress of Electronic Music Distribution creates a natural pressure for fine-grained musical metadata. This metadata is needed to provide music distribution services which are able to cope with the mere size of music catalogues, and the desire of users to access music titles by similarity. In this context, we describe a project of a global music title metadatabase, and focus in the particular "genre" descriptor. We analyze existing taxonomies of musical genre as found in the music industry and on the Internet, and stress on their inconsistencies. We describe a novel music genre taxonomy based on a few guiding principles, and report on the process of building this taxonomy.
Citations
More filters
Journal ArticleDOI
TL;DR: This survey reviews 100+ recent articles on content-based multimedia information retrieval and discusses their role in current research directions which include browsing and search paradigms, user studies, affective computing, learning, semantic queries, new features and media types, high performance indexing, and evaluation techniques.
Abstract: Extending beyond the boundaries of science, art, and culture, content-based multimedia information retrieval provides new paradigms and methods for searching through the myriad variety of media all over the world. This survey reviews 100p recent articles on content-based multimedia information retrieval and discusses their role in current research directions which include browsing and search paradigms, user studies, affective computing, learning, semantic queries, new features and media types, high performance indexing, and evaluation techniques. Based on the current state of the art, we discuss the major challenges for the future.

1,652 citations

Journal ArticleDOI
TL;DR: A computer audition system that can both annotate novel audio tracks with semantically meaningful words and retrieve relevant tracks from a database of unlabeled audio content given a text-based query is presented.
Abstract: We present a computer audition system that can both annotate novel audio tracks with semantically meaningful words and retrieve relevant tracks from a database of unlabeled audio content given a text-based query. We consider the related tasks of content-based audio annotation and retrieval as one supervised multiclass, multilabel problem in which we model the joint probability of acoustic features and words. We collect a data set of 1700 human-generated annotations that describe 500 Western popular music tracks. For each word in a vocabulary, we use this data to train a Gaussian mixture model (GMM) over an audio feature space. We estimate the parameters of the model using the weighted mixture hierarchies expectation maximization algorithm. This algorithm is more scalable to large data sets and produces better density estimates than standard parameter estimation techniques. The quality of the music annotations produced by our system is comparable with the performance of humans on the same task. Our ldquoquery-by-textrdquo system can retrieve appropriate songs for a large number of musically relevant words. We also show that our audition system is general by learning a model that can annotate and retrieve sound effects.

510 citations


Cites background from "A taxonomy of musical genres"

  • ...The assumption of a predefined taxonomy and the explicit labeling of songs into (mutually exclusive) classes can give rise to a number of problems [10] due to the fact that music is inherently subjective....

    [...]

Journal ArticleDOI
TL;DR: This article discusses the various approaches in representing musical genre, and proposes to classify these approaches in three main categories: manual, prescriptive and emergent approaches.
Abstract: Musical genre is probably the most popular music descriptor. In the context of large musical databases and Electronic Music Distribution, genre is therefore a crucial metadata for the description of music content. However, genre is intrinsically ill-defined and attempts at defining genre precisely have a strong tendency to end up in circular, ungrounded projections of fantasies. Is genre an intrinsic attribute of music titles, as, say, tempo? Or is genre a extrinsic description of the whole piece? In this article, we discuss the various approaches in representing musical genre, and propose to classify these approaches in three main categories: manual, prescriptive and emergent approaches. We discuss the pros and cons of each approach, and illustrate our study with results of the Cuidado IST project.

354 citations


Cites background or methods or result from "A taxonomy of musical genres"

  • ...Pachet and Cazaly (2000) compares 3 Internet genre taxonomies: allmusic.com (531 genres), amazon.com (719 genres) and mp3.com (430 genres)....

    [...]

  • ...…Tower Records, Fnac . . . – Music charts: Billboard, Top 50, Cashbox . . . – Musical web sites and online record shops: Amazon, All Music, SonicNet, Mzz, Listen, Netbeat . . . – Specialized press and books – Specialized web radios The complete analysis can be found in Pachet and Cazaly (2000)....

    [...]

  • ...Note that similar conclusions are drawn by Pachet and Cazaly (2000): genre taxonomies are highly non-consistent, and there is no general consensus on genre, especially for this pop/rock distinction....

    [...]

  • ...In the CUIDADO project, we have initially taken this route and built a rather detailed taxonomy of genre for music titles, described in Pachet and Cazaly (2000)....

    [...]

Journal ArticleDOI
TL;DR: The state-of-the-art in automatic genre classification of music collections through three main paradigms: expert systems, unsupervised classification, and supervised classification is reviewed.
Abstract: This paper reviews the state-of-the-art in automatic genre classification of music collections through three main paradigms: expert systems, unsupervised classification, and supervised classification. The paper discusses the importance of music genres with their definitions and hierarchies. It also presents techniques to extract meaningful information from audio data to characterize musical excerpts. The paper also presents the results of new emerging research fields and techniques that investigate the proximity of music genres

327 citations


Cites background from "A taxonomy of musical genres"

  • ...Pachet and Cazaly [2] argue that this semantic confusion within a single taxonomy can lead to redundancies that may not be confusing for human users but that may hardly be solved by automatic systems....

    [...]

  • ...NONAGREEMENT ON TAXONOMIES Pachet and Cazaly [2] showed that a general agreement on genre taxonomies does not exist....

    [...]

  • ...Pachet and Cazaly [2] studied a number of music genre taxonomies used in industry and on the Internet and showed that it is not straightforward to build up such a hierarchy of genres....

    [...]

  • ...In fact, Pachet and Cazaly eventually gave up their initial goal to define a general taxonomy of music genres [2] and Pachet et al....

    [...]

  • ...The work by Pachet and Cazaly [2] for a taxonomy of music genres can be compared to an expert system approach though it did not lead to an actual implementation; yet it is worth mentioning it as it allows a deeper comprehension of the difficulties of music genres classification....

    [...]

Proceedings ArticleDOI
01 Dec 2002
TL;DR: With Islands of Music, a system which facilitates exploration of music libraries without requiring manual genre classification is presented, given pieces of music in raw audio format, their perceived sound similarities based on psychoacoustic models are estimated and organized on a 2-dimensional map.
Abstract: With Islands of Music we present a system which facilitates exploration of music libraries without requiring manual genre classification. Given pieces of music in raw audio format we estimate their perceived sound similarities based on psychoacoustic models. Subsequently, the pieces are organized on a 2-dimensional map so that similar pieces are located close to each other. A visualization using a metaphor of geographic maps provides an intuitive interface where islands resemble genres or styles of music. We demonstrate the approach using a collection of 359 pieces of music.

325 citations


Cites background from "A taxonomy of musical genres"

  • ...The difficulties of such taxonomies have been analyzed, for example, in [19]....

    [...]

References
More filters
Journal ArticleDOI
TL;DR: Book cover plate showing the crest of the Scheurl family (16th century).
Abstract: Book cover plate showing the crest of the Scheurl family (16th century).

295 citations


"A taxonomy of musical genres" refers background or methods in this paper

  • ...In particular, progress in networking transmission, compression of audio, and protection of digital data (Memon and Wong, 1998) allow now or in the near future to deliver quickly and safely music to users in a digital format through networks, either Internet, or digital audio broadcasting....

    [...]

  • ...In this context, we describe a project of a global music title metadatabase, and focus in the particular “genre” descriptor....

    [...]

01 Jan 1999
TL;DR: An overview of the evolution of Protégé is given, examining the methodological assumptions underlying the original ProtÉgé system and discussing the ways in which the methodology has changed over time.
Abstract: It has been 13 years since the first version of Protégé was run. The original tool was a small application, aimed mainly at building knowledge-acquisition tools for a few very specialized programs (it grew out of the ONCOCIN project and the subsequent attempts to build expert systems for protocol-based therapy planning). The most recent version, Protégé-2000, incorporates the Open Knowledge Base Connectivity (OKBC) knowledge model, is written to run across a wide variety of platforms, supports customized user-interface extensions, and has been used by over 300 individuals and research groups, most of whom are only peripherally interested in medical informatics. Researchers not directly involved in the project might well wonder how Protégé evolved, what are the reasons for the repeated reimplementations, and how to tell the various versions apart. In this paper, we give an overview of the evolution of Protégé, examining the methodological assumptions underlying the original Protégé system and discussing the ways in which the methodology has changed over time. We conclude with an overview of the latest version of Protégé, Protégé-2000. 1. MOTIVATION AND A TIMELINE The Protégé applications (hereafter ‘Protégé’) are a set of tools that have been evolving for over a decade, from a simple program which helped construct specialized knowledge-bases to a set of general purpose knowledge-base creation and maintenance tools. While Protégé began as a small application designed for a medical domain (protocol-based therapy planning), it has grown and evolved to become a much more general-purpose set of tools for building knowledge-based systems. The original goal of Protégé was to reduce the knowledge-acquisition bottleneck (Hayes-Roth et al, 1983) by minimizing the role of the knowledge-engineer in constructing knowledge-bases. In order to do this, Musen (1988, 1989b) posited that knowledge-acquisition proceeds in welldefined stages and that knowledge acquired in one stage could be used to generate and customize knowledge-acquisition tools for subsequent stages. In (Musen, 1988), Protégé was defined as an application that takes advantage of this structured information to simplify the knowledgeacquisition process. The original Protégé was described this way (Musen, 1988): Protégé is neither an expert system itself nor a program that builds expert systems directly. Instead, Protégé is a tool that helps users build other tools that are custom-tailored to assist with knowledgeacquisition for expert systems in specific application areas. The original Protégé demonstrated the viability of this approach, and of the use of task-specific knowledge to generate and customize knowledge-acquisition tools. But as with many first-

295 citations


"A taxonomy of musical genres" refers methods in this paper

  • ...Current work concerns focus on the scale-up of the taxonomy and the metadatabase (using automated tools such as Protégé (Grosso et al., 1999) and its effective use for building EMD services....

    [...]

  • ...Grosso, W. E. Eriksson, H. Fergerson, R. W. Gennari, J. H. Tu, S. W. & Musen, M A. Knowledge Modeling at the Millennium (The Design and Evolution of Protege-2000)....

    [...]

Journal ArticleDOI
TL;DR: A novel approach to music selection called RecitalComposer is proposed, which is based on computing coherent sequences of music titles, which amounts to solving a combinatorial pattern generation problem by using constraint satisfaction techniques.
Abstract: Accessing large digital music catalogues raises a problem for both users and content providers. We propose a novel approach to music selection called RecitalComposer, which is based on computing coherent sequences of music titles. This amounts to solving a combinatorial pattern generation problem by using constraint satisfaction techniques.

61 citations

Journal ArticleDOI
TL;DR: This paper suggests how a variety of music-related activities could make use of some existing or quickly maturing content-processing technologies, and focuses on new aspects of listening, interacting with music, finding and comparing music, performing it, editing it, exchanging music with others or selling it, teaching it, analyzing it, and criticizing it.
Abstract: Although the digital processing of music has been a reality for many years – from studio production to home reproduction, from musical instruments to editing – we are still very far from having a clear picture of what role content processing of music is likely to play in tomorrow's music world. Content processing is a general term covering feature extraction and modelling techniques for enabling basic retrieval, interaction, and creation functionality. The aim of using this term is to establish a direct analogy with similar concepts in image and video processing. This paper suggests how a variety of music-related activities could make use of some existing or quickly maturing content-processing technologies. In particular, it focuses on new aspects of listening, interacting with music, finding and comparing music, performing it, editing it, exchanging music with others or selling it, teaching it, analyzing it, and criticizing it.

14 citations


"A taxonomy of musical genres" refers background or methods in this paper

  • ...We describe a novel music genre taxonomy based on a few guiding principles, and report on the process of building this taxonomy....

    [...]

  • ...The need for metadata describing the content of music catalogues has now become crucial, especially in the context of high level search services of electronic music distribution ( Aigrain, 1999)....

    [...]