audio_to_midi
A Convolutional Neural Network which converts piano audio to a simplified MIDI format.The final model takes as input an audio file (mono- or polyphonic)and outputs a simplified MIDI output with the corresponding notes andnote duration. This output can then be reconstructed into a standard MIDI file format.
Main objective
The automated conversion executed by the CNN is a step toward the largergoal of Automatic Music Transcription (AMT). AMT and Music Information Retrieval have many applications in industry, including DigitalAudio Workstation software development and music recommendation systems.
Setup
To get started, download the data from the Saarland Music dataset, putting the audio in one directory named "audio" andthe MIDI in another directory called "midi":
mkdir audio wget "http://resources.mpi-inf.mpg.de/SMD/SMD_MIDI-Audio-Piano-Music.html" -e robots=off -r -l1 -nd --no-parent -A.mp3 mkdir midi wget "http://resources.mpi-inf.mpg.de/SMD/SMD_MIDI-Audio-Piano-Music.html" -e robots=off -r -l1 -nd --no-parent -A.midIn create_dataset.py, in the main function, follow the instructions to set directory_str to the filepath where youdownloaded the dataset.
Run create_dataset.py.
The file models.py contains the code for the final model.
Libraries
TensorFlow install instructions:
https://www.tensorflow.org/install/
Keras install instructions:
https://keras.io/#installation
collections
keras (see instructions above for dependencies)
librosa
math
matplotlib
mido
ntpath
numpy
os
pickle
random
scikit-learn
shutil
tensorflow (see instructions above for dependencies)
time
Issues
On Windows, when loading in the audio files with librosa, the following error may arise:
raise NoBackendError()
audioread.NoBackendError
If the above error is raised, try installing FFmpeg:
https://www.wikihow.com/Install-FFmpeg-on-Windows
On Linux, the equivalent fix is:sudo apt-get install libav-tools
Copyright
Copyright (c) 2018 Lillian Neff
