Comments (4)
从网上下载数据量过大,复现流程过久,我是做NLP的,最近在弄声纹识别,作为一个新手来说,复现流程不是很友好,有一点费劲,如果能提供一份少量voxceleb数据,能够快速复现整体流程,而不需要去一直等数据下载下来才能复现流程。
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那个是转换好的,如果想用在其他领域没有走通整个流程,以及看一下原始的数据样式,感觉用不上,也看了recipe下面的,感觉跑通太难了,FileNotFoundError: [Errno 2] No such file or directory: 'exp/pytorch_xvector_train/config/nnet.config'
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而且原始的数据需要翻墙,我也翻墙了,但是下载的非常慢,感觉如果有少量原始数据到数据转换,模型训练到最后的结果预测,这行对于新手来说友好一些。
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Related Issues (20)
- 多gpu运行 HOT 5
- 百度云盘的voxceleb recipe链接已经失效了,可以重新分享么?
- run Voxceleb Recipe [Speaker Recognition] HOT 3
- subtools/scoreSets.sh中191行特征提取错误数统计值errorNum HOT 1
- 多卡运行报错join() HOT 1
- the num_targets and the max label in train.egs.csv are not equal HOT 1
- Removing deprecated has_key function
- 多卡GPU运行失败 HOT 2
- 想完成一个说话人确认系统,应该怎么开始? HOT 2
- Are there any plans to add the onnx conversion module to the model?
- rirs 和 musan 在哪里下载的?
- train.py,# Recover checkpoint 没有将loss的weight的保存,仅load模型,是不是有问题? HOT 1
- 当使用ResNet模型进行迁移的问题 HOT 1
- subtools/pytorch/pipeline/export_jit_model.sh 导出模型报错 HOT 2
- runtime中的processor打分模块能否开源一下
- 是否准备提供onnx 导出功能的支持 HOT 2
- 发现了一个逻辑漏洞/found a bug
- online训练提示标签越界问题:Assertion `idx_dim >= 0 && idx_dim < index_size && "index out of bounds"`
- subtools/pytorch/model/resnet_xvector.py文件152行多写了一个self x = self.self.cmvn_(x)
- extras/check_dependencies.sh: 13: function: not found HOT 1
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