Musical genre classification of audio signals
Top Cited Papers
- 7 November 2002
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Speech and Audio Processing
- Vol. 10 (5) , 293-302
- https://doi.org/10.1109/tsa.2002.800560
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.Keywords
This publication has 21 references indexed in Scilit:
- Construction and evaluation of a robust multifeature speech/music discriminatorPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Estimating tempo, swing and beat locations in audio recordingsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Tatum grid analysis of musical signalsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Content-based methods for the management of digital musicPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Sound analysis using MPEG compressed audioPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Content-based indexing and retrieval of audio data using waveletsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- The beat spectrum: a new approach to rhythm analysisPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2001
- MARSYAS: a framework for audio analysisOrganised Sound, 2000
- Content-based audio classification and retrieval using the nearest feature line methodIEEE Transactions on Speech and Audio Processing, 2000
- Tempo and beat analysis of acoustic musical signalsThe Journal of the Acoustical Society of America, 1998