Music Genre Estimation from Low Level Audio Features

Allamanche E, Kastner T, Wistorf R, Lefebvre N, Herre J. Music Genre Estimation from Low Level Audio Features. In: AES Conference: 25th International Conference: Metadata for Audio. Audio Engineering Society; 2004. Paper 6-3. Available from: https://aes.org/publications/elibrary-page/?id=12820

@inproceedings{Allamanche2004_12820,
  author = {Allamanche, Eric and Kastner, Thorsten and Wistorf, Ralf and Lefebvre, Nicolas and Herre, Juergen},
  title = {{Music Genre Estimation from Low Level Audio Features}},
  booktitle = {AES Conference: 25th International Conference: Metadata for Audio},
  note = {Paper 6-3},
  year = {2004},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=12820}
}

TY  - CPAPER
TI  - Music Genre Estimation from Low Level Audio Features
AU  - Allamanche, Eric
AU  - Kastner, Thorsten
AU  - Wistorf, Ralf
AU  - Lefebvre, Nicolas
AU  - Herre, Juergen
T2  - AES Conference: 25th International Conference: Metadata for Audio
M1  - Paper 6-3
PY  - 2004
DA  - 2004/06/06
UR  - https://aes.org/publications/elibrary-page/?id=12820
PB  - Audio Engineering Society
LA  - en
AB  - Despite the subjective nature of associating a certain song or artist with a specific musical genre, this type of characterization is frequently used to provide a convenient way of expressing very coarse information on the basic stylistic and rhythmic elements and/or instrumentation of a song. An audio database which is structured according to different musical genres is the first important step to provide an easy/intuitive access to a large music collection. Thus, a convenient way for indexing large databases by musical genre is desired. This paper describes a system which automatically classifies music into several musical genres. Different features as well as classification strategies will be evaluated and compared. The system's performance is assessed by means of a subjective listening test.
ER  -