Music genre classification of audio signals
| dc.contributor.author | Tzanetakis, George | |
| dc.contributor.author | Perry, Cook | |
| dc.date.accessioned | 2009-02-14T00:27:50Z | |
| dc.date.available | 2009-02-14T00:27:50Z | |
| dc.date.issued | 2002-07 | |
| dc.description | ©2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | en_US |
| dc.description.abstract | Musical genres are categorical labels created by humans to characterize pieces of music. A musical genre is characterized by the common characteristics shared by its members. These characteristics typically are related to the instrumentation, rhythmic structure, and harmonic content of the music. Genre hierarchies are commonly used to structure the large collections of music available on the Web. Currently musical genre annotation is performed manually. Automatic musical genre classification can assist or replace the human user in this process and would be a valuable addition to music information retrieval systems. In addition, automatic musical genre classification provides a framework for developing and evaluating features for any type of content-based analysis of musical signals. In this paper, the automatic classification of audio signals into an hierarchy of musical genres is explored. More specifically, three feature sets for representing timbral texture, rhythmic content and pitch content are proposed. The performance and relative importance of the proposed features is investigated by training statistical pattern recognition classifiers using real-world audio collections. Both whole file and real-time frame-based classification schemes are described. Using the proposed feature sets, classification of 61% for ten musical genres is achieved. This result is comparable to results reported for human musical genre classification. | en_US |
| dc.identifier.citation | G. Tzanetakis and P. Cook "Musical Genre Classification of Audio Signals", IEEE Transactions on Speech and Audio Processing , 10(5), July 2002 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/1344 | |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE | en_US |
| dc.subject | Audio classification | |
| dc.subject | Beat Analysis | |
| dc.subject | feature extraction | |
| dc.subject | musical genre classification | |
| dc.subject | wavelets | |
| dc.subject.department | Department of Computer Science | |
| dc.title | Music genre classification of audio signals | en_US |
| dc.type | Article | en_US |