HipHop Genealogy: Difference between revisions
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A list of each artist in the dataset. Rather than extracted from tags in the mp3 file, they are hand-entered via <tt>categorize.py</tt> to ensure correct normalization. | A list of each artist in the dataset. Rather than extracted from tags in the mp3 file, they are hand-entered via <tt>categorize.py</tt> to ensure correct normalization. | ||
* compressed | * compressed | ||
Loosely organized directory of mp3/m4a/etc. files for the base data set. | Loosely organized directory of mp3/m4a/etc. files for the base data set. New data set examples go in here, to be sorted out by <tt>categorized.py</tt>. | ||
* genres.json | * genres.json | ||
List of each possible genre in the dataset. Handwritten and used by <tt>categorize.py</tt> for manual genre entry. | List of each possible genre in the dataset. Handwritten and used by <tt>categorize.py</tt> for manual genre entry. |
Revision as of 09:06, 10 November 2013
In /usr/ccrma/media/databases/hiphop-gene/ are the following files:
Data Files
- artists.json
A list of each artist in the dataset. Rather than extracted from tags in the mp3 file, they are hand-entered via categorize.py to ensure correct normalization.
- compressed
Loosely organized directory of mp3/m4a/etc. files for the base data set. New data set examples go in here, to be sorted out by categorized.py.
- genres.json
List of each possible genre in the dataset. Handwritten and used by categorize.py for manual genre entry.
- meta.json
The main catalogue of metadata associated with each WAV file. Currently includes genre and artist(s) info, in addition to file paths of compressed/WAV versions of the audio data.
- wav
Directory of uncompressed audio data files. Automatically populated by decompress.py
Utility Tools
- decompress.py
Convert files in compressed/ to WAV format, and place them in wav/.
- build_artists.py
Add any new artists in meta.json to artists.json (normally not necessary as categorize.py should do this automatically).
- categorize.py
Search for new files in compressed/ and request genre and artist information. Stores this all in meta.json.
- export_mat.py
Export meta.json data into a format convenient for use in Matlab.