Description:
Dear Author,
Hello! I am currently using the SimpleDiarization project for speaker diarization tasks and attempting to reproduce the results you provided on the VoxConverse dataset. I followed the installation and configuration instructions in the README file, but my results differ from the default results you provided. I would like to ask if there are any specific configurations or dependency versions that I should pay special attention to, or if I have missed any steps.
My Environment and Steps:
Operating System: macOS
Python Version: 3.11
Dependency Versions:
pyannote.audio==3.3.2
speechbrain==1.0.3
scikit-learn==1.7.1
torch==2.7.1
tqdm==4.67.1
pyyaml==6.0.2
My Results:
Development Set (dev):
OVERALL DER : 5.90% JER : 17.17%
Test Set (test):
OVERALL DER : 8.43% JER : 25.04%
My Questions:
- My results differ from the default results you provided, especially the JER value for the test set. Have I missed any steps or do I need to adjust certain configurations?
- Are there any other suggestions or considerations that could help me reproduce your results?
Thank you very much for your help and support!
Description:
Dear Author,
Hello! I am currently using the SimpleDiarization project for speaker diarization tasks and attempting to reproduce the results you provided on the VoxConverse dataset. I followed the installation and configuration instructions in the README file, but my results differ from the default results you provided. I would like to ask if there are any specific configurations or dependency versions that I should pay special attention to, or if I have missed any steps.
My Environment and Steps:
Operating System: macOS
Python Version: 3.11
Dependency Versions:
pyannote.audio==3.3.2
speechbrain==1.0.3
scikit-learn==1.7.1
torch==2.7.1
tqdm==4.67.1
pyyaml==6.0.2
My Results:
Development Set (dev):
OVERALL DER : 5.90% JER : 17.17%
Test Set (test):
OVERALL DER : 8.43% JER : 25.04%
My Questions:
Thank you very much for your help and support!