Torchopenl3

Please cite the following TorchOpenL3 in your work:
[1]Gyanendra Das, Humair Raj Khan, Joseph Turian (2021). torchopenl3 (version 1.0.1). DOI 10.5281/zenodo.5168808, https://github.com/torchopenl3/torchopenl3.

TorchopenL3 is a pytorch port of the OpenL3 Python library for computing deep audio embeddings.

Contributors

Please refer to the Openl3 Library for keras version.

Comparison

We run torchopenl3 over 100 audio files and compare with openl3 embeddings. Below is the MAE (Mean Absolute Error) Table

Installation

Install via pip

pip install torchopenl3

Install the package with all dev libraries (i.e. tensorflow openl3)

git clone https://github.com/turian/torchopenl3.git
pip3 install -e ".[dev]"

Install Docker and work within the Docker environment. Unfortunately this Docker image is quite big (about 4 GB) because

docker pull turian/torchopenl3
# Or, build the docker yourself
#docker build -t turian/torchopenl3 .

Using TorchpenL3

To help you get started with TorchopenL3 please go through the colab file.

Acknowledge

Special Thank you to Joseph Turian for his help

[1] Look, Listen and Learn More: Design Choices for Deep Audio Embeddings
Jason Cramer, Ho-Hsiang Wu, Justin Salamon, and Juan Pablo Bello.
IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pages 3852–3856, Brighton, UK, May 2019.

[2] Look, Listen and Learn
Relja Arandjelović and Andrew Zisserman
IEEE International Conference on Computer Vision (ICCV), Venice, Italy, Oct. 2017.

Model Weights License

The model weights are made available under