Comments (5)
BancoLin
commented on July 3, 2024
1
report my results:
- use ffmpeg to downsample the source data from 48khz to 16khz.
- use pretrained model in the best_ckpt/ folder
- use CPU to do evaluation
In the following metrics the first numbers are from the TABLE I of the paper (https://arxiv.org/pdf/2209.11112.pdf), and the second ones are my results. All the results are similar except the SSNR.
PESQ: 3.41 --> 3.41
CSIG: 4.63 --> 4.67
CBAK: 3.94 --> 3.91
COVL: 4.12 --> 4.14
SSNR: 11.10 --> 10.68
STOI: 0.96 --> 0.96
despite the inconsistent numbers between code and paper, i'm quite satisfied the performance with our own data.
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utyanndesu
commented on July 3, 2024
We encountered the same problem, with the SSNR indicator only 10.4 and each indicator slightly lower
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SherifAbdulatif
commented on July 3, 2024
We got some complains about SSNR and it is currently being checked.
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moshengmao
commented on July 3, 2024
- use ffmpeg to downsample the source data from 48khz to 16khz
I want to ask if I use the VCTK-DEMAND dataset to train, whether I need downsample the trainset to 16khz first or input the original data.
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SherifAbdulatif
commented on July 3, 2024
You need to downsample the data first.
…On Fri, 17 Nov 2023, 2:39 am moshengmao, ***@***.***> wrote:
- use ffmpeg to downsample the source data from 48khz to 16khz
I want to ask if I use the VCTK-DEMAND dataset to train, whether I need
downsample the trainset to 16khz first or input the original data.
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Related Issues (20)
- RuntimeError: NCCL error in: /……/.cpp:957, invalid usage, NCCL version 21.0.3 HOT 5
- RuntimeError: permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 3 is not equal to len(dims) = 4 HOT 1
- RuntimeError HOT 3
- the change of gen_loss during training HOT 1
- RuntimeError
- RuntimeError HOT 2
- About the decreasing of loss HOT 1
- Can not reproduce the results HOT 12
- Training can get stuck HOT 6
- Inferior results trained from scratch HOT 7
- RuntimeeError HOT 1
- Can not reproduce the results HOT 3
- Training GPU requirements
- File "pesq/cypesq.pyx", line 1, in init cypesq ImportError: numpy.core.multiarray failed to import (auto-generated because you didn't call 'numpy.import_array()' after cimporting numpy; use '<void>numpy._import_array' to disable if you are certain you don't need it)
- File "/anaconda3/envs/cmg/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 578, in __init__ dist._verify_model_across_ranks(self.process_group, parameters) RuntimeError: NCCL error in: ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:957, invalid usage, NCCL version 21.0.3 ncclInvalidUsage: This usually reflects invalid usage of NCCL library (such as too many async ops, too many collectives at once, mixing streams in a group, etc). HOT 2
- How do you resample to 16000?
- 时域Loss计算疑惑
- the training speed confusion
- My server has a 3090, but reports that I don't have a gpu HOT 1
- Test set requirements when training
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