Synergistic audio pre-processing and neural architecture design maximizes performance

This repository contains the code for the paper titled "Synergistic audio pre-processing and neural architecture design maximizes performance".

Python Version

Python version: 3.10.12

Installation

To set up the environment, run the following commands:

python3 -m venv .venv
pip install nni torch torchvision torchaudio pytorch_lightning fcwt matplotlib

Datasets

The datasets are automatically downloaded when running the run_experiments.py script for the first time on a specific dataset.

Running Experiments

To reproduce our results, you can execute the following steps:

OptModel

To run the OptModel experiment, use the following command:

python run_experiment.py --experiment 1 --dataset [speech_commands, vocal_sound, spoken100]

OptPre

To run the OptPre experiment, use the following command:

python run_experiment.py --experiment 2 --dataset [speech_commands, vocal_sound, spoken100] --model [mobilenetv2, mobilenetv3small, mobilenetv3large]

OptBoth

To run the OptBoth experiment, use the following command:

python run_experiment.py --experiment 3 --dataset [speech_commands, vocal_sound, spoken100]