The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Representing Musical Genre: A State of the Art
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Neural networks for pattern recognition
(1994) · Choice Reviews Online · doi:10.5860/choice.31-5500 · Cited by 18,538
Neural Networks for Pattern Recognition
Bishop, C. M. (1995) · doi:10.1093/oso/9780198538493.001.0001 · Cited by 12,287
Fundamentals of speech recognition
Rabiner, L. R., & Juang, B.-H. F. (1993) · Cited by 7,680
Growing Artificial Societies: Social Science from the Bottom Up
Fukuyama, F., Epstein, J., & Axtell, R. (1996) · Foreign Affairs · doi:10.2307/20048043 · Cited by 3,708
Social information filtering: algorithms for automating “word of mouth”
Shardanand, U., & Maes, P. (1995) · Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '95 · doi:10.1145/223904.223931 · Cited by 2,823
Growing artificial societies: Social science from the bottom up
(1997) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(97)82923-9 · Cited by 1,646
Growing Artificial Societies: Social Science from the Bottom Up
Duffy, J., Epstein, J. M., & Axtell, R. (1998) · Southern Economic Journal · doi:10.2307/1060800 · Cited by 1,070
Content-based classification, search, and retrieval of audio
Wold, E., Blum, T., Keislar, D., & Wheaten, J. (1996) · IEEE Multimedia · doi:10.1109/93.556537 · Cited by 789
The Continuator: Musical Interaction With Style
Pachet, F. (2003) · Journal of New Music Research · doi:10.1076/jnmr.32.3.333.16861 · Cited by 338
Self-citationAutomatic Musical Genre Classification Of Audio Signals.
Tzanetakis, G. (2001) · doi:10.5281/zenodo.1415057 · Cited by 299
Metadata
- Authors
- Aucouturier, J.-J., & Pachet, F.
- Venue
- Journal of New Music Research
- Publisher
- Informa UK Limited
- Published
- 2003-03-01
- Volume
- 32
- Issue
- 1
- Pages
- 83-93
- ISSN
- 0929-8215 (ISSN-L)
- OpenAlex
- W2159561775
- Cited by
- 369
- References
- 14
- FWCI
- 32.28
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Representing Musical Genre: A State of the Art. https://app.cochat.ai/papers/10.1076/jnmr.32.1.83.16801
- The paper
- Aucouturier, J.-J., & Pachet, F. (2003). Representing Musical Genre: A State of the Art. Journal of New Music Research. https://doi.org/10.1076/jnmr.32.1.83.16801
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
