TaoRuijie / ECAPA-TDNN

Unofficial reimplementation of ECAPA-TDNN for speaker recognition (EER=0.86 for Vox1_O when train only in Vox2)
MIT License
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model. files #66

Closed Time-slice closed 11 months ago

Time-slice commented 1 year ago

What is the process of generating model1,2,3~n files, I have been running for 24 hours, only generated three model files, and I have not started training

TaoRuijie commented 1 year ago

What does your meaning for three model files, model_0001.model? ...0003.model?

check your gpu usage condition during training

Time-slice commented 1 year ago

三个模型文件 model_0001.model 的含义是什么?...0003.型号? Yes, model 0001.model,Is the process of generating training?It is very slow to generate them, about 10 hours to generate one, and the utilization rate of GPU is 0, what is the reason? 训练时检查你的GPU使用情况

TaoRuijie commented 1 year ago

1是第一个epoch后的model文件,2是第二个 以此类推

检查你的gpu使用率

详情可以看这个视频 https://www.bilibili.com/video/BV1dF411g7t1/?share_source=copy_web&vd_source=51a0a7cde6b6ec9e7d1c2cacdb0aaa9d

Time-slice commented 1 year ago

Thank you very much,your code and video have been very helpful to me

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1是第一个epoch后的model文件,2是第二个 以此类推

检查你的gpu使用率

详情可以看这个视频 https://www.bilibili.com/video/BV1dF411g7t1/?share_source=copy_web&vd_source=51a0a7cde6b6ec9e7d1c2cacdb0aaa9d

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Time-slice commented 11 months ago

Hello, Mr. Black, I am a new researcher in the field of speaker recognition, and I have two questions to ask you:

  1. I noticed that some papers use 40 dimensions of Fbank feature, and some use 80 dimensions

2. Speed Perturb for data augmentation

Do these two items have a big impact on EER?

I would appreciate it if you could give me your answer !

 

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TaoRuijie commented 11 months ago
  1. I noticed that some papers use 40 dimensions of Fbank feature, and some use 80 dimensions This effect a bit, not so huge. 2. Speed Perturb for data augmentation In VoxCeleb2, effect is limited, in CnCeleb, it can improve a lot.