PyNeuralFx: A Python Package for Neural Audio Effect Modeling

TL;DR

PyNeuralFx is an open-source Python toolkit that facilitates research and comparison of neural audio effect models, promoting reproducibility and in-depth analysis through standardized architectures and visualization tools.

Contribution

It introduces a comprehensive, standardized framework for neural audio effect modeling in Python, enhancing reproducibility and performance analysis capabilities.

Findings

Provides a suite of well-established model architectures

Includes visualization tools for model analysis

Promotes reproducibility in neural audio effect research

Abstract

We present PyNeuralFx, an open-source Python toolkit designed for research on neural audio effect modeling. The toolkit provides an intuitive framework and offers a comprehensive suite of features, including standardized implementation of well-established model architectures, loss functions, and easy-to-use visualization tools. As such, it helps promote reproducibility for research on neural audio effect modeling, and enable in-depth performance comparison of different models, offering insight into the behavior and operational characteristics of models through DSP methodology. The toolkit can be found at https://github.com/ytsrt66589/pyneuralfx.