Instrument streaming

This repo contains the instrument streaming model presented in the paper: Yun-Ning Hung, Yi-An Chen and Yi-Hsuan Yang, "MULTITASK LEARNING FOR FRAME-LEVEL INSTRUMENT RECOGNITION"

Demo

Related websites:

• Project website
• Music Transcription Overview
• Instrument Activity Detection

Musescore dataset

• parse_data.py contains the function to parse the Musescore dataset
• dataset statistic.xlsx contains the statistic of Musescore dataset

Run the prediction

1. Put MP3/WAV files in the "mp3" folder
2. Run the 'prediction.py' with the name of the song as the first arg

python3 prediction.py ocean.mp3

Instrument, pitch and pianorolls prediction result will be stored in the output_data folder

Convert pianorolls to MIDI

• Run the 'output_midi.py' with the name of the pianorolls as the first arg

python3 output_midi.py ocean.npy

Train the model

• run.py: start the training
• loadData.py: load the data from dataset
• lib.py: some utilities such as loss function and dataloader
• fit.py: trainer
• model.py: model's structure
• block.py: model's block structure
• structure.py: model's parameters