Brainharmonic - Generating music from brain signal data using deep learning #135
Labels
bhg:melbourne_aus_1
BHG 2021 Australasia event
git_skills:1_commit_push
git_skills:2_branches_PRs
modality:EEG
modality:fMRI
modality:MRI
programming:documentation
Markdown, Sphinx
programming:Python
project_development_status:0_concept_no_content
project_type:coding_methods
project_type:data_management
involves programming
project_type:documentation
project_type:method_development
project_type:pipeline_development
project
status:published
status:web_ready
tools:fMRIPrep
tools:Freesurfer
topic:deep_learning
topic:information_theory
topic:machine_learning
Title
Brainharmonic - Generating music from brain signal data using deep learning
Leaders
Collaborators
No response
Brainhack Global 2021 Event
Brainhack Australasia
Project Description
This project aims to develop a tool to generate music from brain signals using deep learning models. There has been a lot of work on generating new music from a large collection of music using deep AI models, as well as some work on generating music from brain EEG/fMRI signal through algorithmic or rule based approaches. However there has not been work done on using deep learning models to generate music from EEG/fMRI signal.
In this project, we will use deep generative models to allow EEG/fMRI data to be used as an input to generate music. We will also look into linking brain signal from different regions of the brain to different instruments to create a symphony. More details of the design can be found on our Github page.
Link to project repository/sources
https://github.com/marianocabezas/brainharmonic
Goals for Brainhack Global
Develop a tool to generate songs from EGG/fMRI brain signals using deep learning
Good first issues
Develop a generative deep learning model to generate songs from a latent space
Develop a deep learning model to translate EEG/fMRI sequences from similar subjects into a latent space
Communication channels
https://mattermost.brainhack.org/brainhack/channels/brainharmonic
Skills
Onboarding documentation
No response
What will participants learn?
Data to use
No response
Number of collaborators
2
Credit to collaborators
Project contributors are credited on Readme file on project Github page
Image
Type
coding_methods, data_management, method_development, pipeline_development
Development status
0_concept_no_content
Topic
deep_learning, information_theory, machine_learning
Tools
fMRIPrep, Freesurfer
Programming language
Python
Modalities
EEG, fMRI
Git skills
1_commit_push, 2_branches_PRs
Anything else?
No response
Things to do after the project is submitted.
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