:bangbang: This repository has been replaced with a newer release of the Clarity code that supports all Clarity Challenges: CEC1, CPC1 and the current challenge CEC2. Please redirect to https://github.com/claritychallenge/clarity . :bangbang:
In this repository, you will find code to support all Clarity Challenges
Data for the challenges is available separately. See specific instructions in each challenge sub-directory, or visit the challenge website.
For further details of the Clarity Project visit, claritychallenge.org.
When I run ./install.sh and download HRIR data, the wget request seems to get a html file instead of a tar.gz file. Could you give me some advices about how to get the HRIR data? Thank you!
I'm trying to run the baseline scripts as suggested in your INSTALL.md file. When running the following code at step 1:
cd install
./install.sh
I have changed the following lines of code to point to my local directory: ```
CLARITY_ROOT=$(/Users/adwayk/Documents/GitHub/clarity_CC/clarity_CPC1/install) # up one level from install script
echo $CLARITY_ROOT
```
I get an error on my system that states that:
Would really appreciate any help soon.
Software to support the Clarity Enhancement and Prediction Challenges.
Python tools are provided for • Mixing scenes to generate the training and development data • Running the baseline hearing aid processing using the Oldenburg/Hoertech open Master Hearing Aid (openMHA) software platform • Running signals through a python implementation of the Moore, Stone, Baer and Glasberg (MSBG) hearing loss model • Estimating intelligibility using the Modified Binaural Short-Time Objective Intelligibility measure (MBSTOI).
This version includes • The first release of the code for supporting the recently opened 1st Clarity Prediction Challenge (CPC1) • Code for supporting the (now closed) 1st Clarity Enhancement Challenge (CEC1)
Software to support the Clarity Enhancement Challenge.
Python tools are provided for • Mixing scenes to generate the training and development data • Running the baseline hearing aid processing using the Oldenburg/Hoertech open Master Hearing Aid (openMHA) software platform • Running signals through a python implementation of the Moore, Stone, Baer and Glasberg (MSBG) hearing loss model • Estimating intelligibility using the Modified Binaural Short-Time Objective Intelligibility measure (MBSTOI).
This version includes • Fixes to construction of anechoic reference signals • Fixes to minor errors in baseline enhancement system • Addition of soft-clipper to baseline hearing aid configuration.
Software to support the Clarity Enhancement Challenge.
Python tools are provided for - Mixing scenes to generate the training and development data - Running the baseline hearing aid processing using the Oldenburg/Hortech open Master Hearing Aid (openMHA) software platform. - Running signals through a python implementation of the Moore, Stone, Baer and Glasberg (MSBG) hearing loss model - Estimating intelligibility using the Modified Binaural Short-Time Objective Intelligibility measure (MBSTOI).
Machine learning challenges for hearing aid processing. UKRI-funded project.
GitHub Repository Homepagehearing-aids machine-learning speech-processing speech-intelligibility