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Machine learning challenges for hearing aid processing

drawing Cadenza Challenge

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We are organising a series of machine learning challenges to enhance hearing-aid signal processing and to better predict how people perceive speech-in-noise (Clarity) and speech-in-music (Cadenza). For further details of the Clarity Project visit the Clarity project website, and for details of our latest Clarity challenges visit our challenge documentation site. You can contact the Clarity Team by email at [email protected]. For further details of the Cadenza Project visit the Cadenza project website, and to find out about the latest Cadenza challenges join the Cadenza Challenge Group.

In this repository, you will find code to support all Clarity and Cadenza Challenges, including baselines, toolkits, and systems from participants. We encourage you to make your system/model open source and contribute to this repository.

Current Events

  • The 2nd Cadenza Challenge is now open 🔥🔥
  • The 3rd Clarity Enhancement Challenge is now open. 🔥🔥
  • The 2nd Clarity Prediction Challenge (CPC2) is now closed.
  • The 4th Clarity Workshop will be held as a satellite event of Interspeech 2023. For details visit the workshop website.

Installation

PyPI

Clarity is available on the Python Package Index (PyPI) to install create and/or activate a virtual environment and then use pip to install.

conda create --name clarity python=3.8
conda activate clarity

pip install pyclarity

GitHub Cloning

# First clone the repo
git clone https://github.com/claritychallenge/clarity.git
cd clarity

# Second create & activate environment with conda, see https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html
conda create --name clarity python=3.8
conda activate clarity

# Last install with pip
pip install -e .

GitHub pip install

Alternatively pip allows you to install packages from GitHub sources directly. The following will install the current main branch.

pip install -e git+https://github.com/claritychallenge/clarity.git@main

Challenges

Current challenge

Previous challenges

Available tools

We provide also a number of tools in this repository:

In addition, differentiable approximation to some tools are provided:

Open-source systems