turian/torchopenl3 repository overview

⁠Torchopenl3

TorchopenL3 is an open-source Python library Pytorch Support for computing deep audio embeddings.

⁠Contributors

Please refer to the Openl3 Library⁠ for keras version.

The audio and image embedding models provided here are published as part of [1], and are based on the Look, Listen and Learn approach [2]. For details about the embedding models and how they were trained, please see:

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.

⁠Comparasion

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 git+https://github.com/turian/torchopenl3.git

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.