kamel402 / maqamnet Goto Github PK

MaqamNet is a model that can predict the mqam type of a given audio file.
The model trained on 4 types out of 8 existed types, which are Risat, Hijaz, Sika, and Ajam.

Because I didn't find any Dataset of maqamat, I collected a few audio files from YouTube, and because of the privacy issue I can't share this Dataset, but you can make your own Data.

9 1D conv layers and input sample size of 59049 (~3 seconds)

• Fix config.py file
• Data processing
  • run python audio_processor.py : audio (to read audio signal from mp3s and save as npy)
  • run python annot_processor.py : annotation (process redundant tags and select top N=4 tags)
    • this will create and save train/valid/test annotation files
• Training
  • You can set multigpu option by listing all the available devices
  • Ex. python main.py --gpus 0 1
  • Ex. python main.py will use 1 gpu if available as a default

• run python eval_tags.py --gpus 0 1 --mp3_file "path/to/mp3file/to/predict.mp3"

• https://github.com/jongpillee/sampleCNN
• https://github.com/tae-jun/sample-cnn
• https://github.com/keunwoochoi/magnatagatune-list
• https://github.com/kyungyunlee/sampleCNN-pytorch