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Neural Resonator

Rigid-Body Sound Synthesis with Differentiable Modal Resonators

This is the code for the paper Rigid-Body Sound Synthesis with Differentiable Modal Resonators. It contains the implementation of the differentiable modal resonator networks, as well as the code to train them and generate the audio samples used in the paper.

Install

To install the package, run the following command:

pip install -e '.[dev]'

Train

For a quicker preview of the training process, please refer to this notebook.

In order to train the network first we need to generate the dataset. Training the network requires large dataset the generation and the training might take up to a day to complete. To do so, run the following command (adjusting the number of shapes and materials to generate):

generate_dataset \
n_train_shapes=500 \
n_val_shapes=20 \
n_test_shapes=20 \
n_train_materials=500 \
n_val_materials=20 \
n_test_materials=20 \
++paths.data_dir=./data

To train the network, run the following command:

train \
++datamodule.sample_rate=32000 \
++datamodule.batch_size=64 \
++datamodule.num_workers=8 \
++datamodule.train_index_map_path=./data/materials_shapes_train/index_map.csv \
++datamodule.val_index_map_path=./data/materials_shapes_val/index_map.csv \
++datamodule.test_index_map_path=./data/materials_shapes_val/index_map.csv \
seed=3407