You are currently logged in as an
Institutional Subscriber.
If you would like to logout,
please click on the button below.
Home / Publications / E-library page
Only AES members and Institutional Journal Subscribers can download
Automated genre classification makes it possible to determine the musical genre of an incoming audio waveform. One application of this is to help listeners find music they like more quickly among millions of tracks in an online music store. By using numerical thresholds and the MPEG-7 descriptors, a computer can analyze the audio stream for occurrences of specific sound events such as kick drum, snare hit, and guitar strum. The knowledge about sound events provides a basis for the implementation of a digital music genre classifier. The classifier inputs a new audio file, extracts salient features, and makes a decision about the musical genre based on the decision rule. The final classification results show a recognition rate in the range 75% - 94% for five genres of music
Author (s): Osmanovic, Nermin
Affiliation:
Microsoft Corporation
(See document for exact affiliation information.)
AES Convention: 125
Paper Number:7513
Publication Date:
2008-10-06
Import into BibTeX
Session subject:
Analysis and Synthesis of Sound
Permalink: https://aes2.org/publications/elibrary-page/?id=14665
(696KB)
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member Join the AES. If you need to check your member status, login to the Member Portal.
Osmanovic, Nermin; 2008; Classification of Musical Genres Using Audio Waveform Descriptors in MPEG-7 [PDF]; Microsoft Corporation; Paper 7513; Available from: https://aes2.org/publications/elibrary-page/?id=14665
Osmanovic, Nermin; Classification of Musical Genres Using Audio Waveform Descriptors in MPEG-7 [PDF]; Microsoft Corporation; Paper 7513; 2008 Available: https://aes2.org/publications/elibrary-page/?id=14665