Comments (1)
Thanks for your interest in our work, I re-downloaded the MP-SENet code in this repo and generated speech with librosa
and soundfile
respectively. After calculating results by cal_metrics.py
, the objective results of both read methods are the same, namely
- pesq: 3.495735651659734
- csig: 4.727512378614241
- cbak: 3.950338723236475
- covl: 4.224942893521928
- ssnr: 10.640891073683255
- stoi: 0.9602032202555391.
These results are consistent with our Interspeech paper. So, this issue is not related to thesoundfile
. Perhaps you can check if your dataset is consistent with ours.
from mp-senet.
Related Issues (20)
- 去混响数据集会公开吗? HOT 11
- Dereverberation HOT 1
- 请问有什么降低MetricLoss的好方法吗 HOT 2
- Weights trained on DNS HOT 2
- Performance with PCS HOT 1
- Questions with regards to reproducing training and inference result HOT 2
- NS and BE(SR) in one model design HOT 1
- Complex loss calculated using compressed magnitude HOT 2
- Error dividing by zero if noisy_audio is silence HOT 1
- About Time Loss And STFT Consistency Loss HOT 2
- conformer structure
- 在自己的数据集上训练学不到信号的高频部分,PESQ提升缓慢
- Out of Memory when inferencing with 60secs file HOT 2
- Gradio Demo App on HuggingFace Spaces with ZeroGPU Support HOT 1
- performance scores
- Question on Bandwidth extension task formulation HOT 3
- OutOfMemoryError HOT 3
- Use for Music? HOT 1
- 这个和DFN哪个效果好?
- Training on a more diverse dataset
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