2005:Audio Artist
From MIREX Wiki
Description
The automatic artist identification of musical audio.
1) Input data The input for this task is a set of sound file excerpts adhering to the format, meta data and content requirements mentioned below.
Audio format:
- CD-quality (Wave, 16-bit, 44100 Hz or 22050 Hz, Mono or Stereo)
- Whole files, algorithms may use segments at authors discretion
Audio content:
- 3 databases: Epitonic, Magantune and USPOP2002
- data set should include at least 75 different artists or groups working in any genre
- both live performances and sequenced music are eligible
- Each artist should be represented by a minimum of 10 examples.
- Would be good to enforce some sort of cross-album component for the actual contest to avoid producer detection
- A tuning database will NOT be provided. However the RWC Magnatune database used for the 2004 Audio desciption contest is still available (Training part 1 [1], Training part 2 [2])
Metadata:
- By definition each example must have an artist or group label corresponding to one of the output classes.
- It is assumed that artist labels will be correct
- The genre label may also be supplied
- The training set should be defined by a text file with one entry per line, in the following format (<> should be omitted, used here for clarity):
<example path and filename>\t<artist label>\t<genre label>\n
2) Output results
- Results should be output into a text file with one entry per line in the following format:
<example path and filename>\t<artist classification>\n
3) Maximum running time
- The maximum running time for a single iteration of a submitted algorithm will be 24 hours (allowing a maximum of 72 hours for 3-fold cross-validation)
