- Emanuele Goat
- Federico Pellizzaro
- Giovanni Zanin
AI-based tool for supporting artists' creativity
Example:
- Generation of book or music album covers
- Book illustrations
- Songwriting
...
For the specific case of guitarists, a model has been trained to recognize which effects have been applied to a guitar sound. The best accuracy found on the test set was ~75%.
Due to the dataset limitations, the model in this repo can currently recognize just one effect applied to a guitar sound. However, the CNN has been studied and developed so that a model can be trained with a dataset where multiple sound effects are applied to a guitar sound.
Additionally, a small web app has been developed to showcase the model's response when given random guitar sounds sourced from the internet.
In order to have the web app running you need conda and then:
- conda env create -f environment.yml
- conda activate kitar-kit-env
- streamlit run .\KitaraKitWebApp.py
