Comments (7)
TaoRuijie
commented on August 19, 2024
请check这里 #34 (comment) mse的内容可以参考对应文章
Beijing ZKJ-NPU Speaker Verification System for VoxCeleb Speaker Recognition Challenge 2021
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JJun-Guo
commented on August 19, 2024
请check这里 #34 (comment) mse的内容可以参考对应文章
Beijing ZKJ-NPU Speaker Verification System for VoxCeleb Speaker Recognition Challenge 2021
好的，感谢您的回复！如果我对模型进行fine-tune一个新的speaker的话，n_class这个参数是不是设为1就可以了？
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TaoRuijie
commented on August 19, 2024
理论上我并不觉得这么finetune是合理的
即使要要这么做，也要在dataloader里把新的speaker赋予大于原speaker数目的类别标签，如5995.
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JJun-Guo
commented on August 19, 2024
理论上我并不觉得这么finetune是合理的
即使要要这么做，也要在dataloader里把新的speaker赋予大于原speaker数目的类别标签，如5995.
您觉得不合理是指speaker的数量太少会使模型坍塌到该speaker吗？还是说finetune的数据量（speaker下的语音数据）不能过小？
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TaoRuijie
commented on August 19, 2024
我没有读过用多一类来finetune的做法 所以我不能确定会有好的结果
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JJun-Guo
commented on August 19, 2024
我没有读过用多一类来finetune的做法 所以我不能确定会有好的结果
明白！您尝试过将vad应用到声纹识别场景吗？理论上是需要vad去除一些干扰音再进行比对？
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TaoRuijie
commented on August 19, 2024
voxceleb2不需要这一步，请阅读一些比赛的相关的报告
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Related Issues (20)
- Vox1_E and Vox1_H HOT 6
- 算法正确率并不高？ HOT 1
- 门限确定和score的分布
- AS-Norm HOT 3
- Online augmentation affects speed HOT 1
- GPU问题 HOT 1
- How to evaluate your nn HOT 3
- EER 15%? HOT 2
- 单卡改多卡 HOT 1
- Code using HOT 1
- AS-norm
- ECAPA-TDNN HOT 1
- 如何解决训练较慢 HOT 2
- 模型收敛慢 HOT 3
- 数据集如何下载 HOT 1
- save model HOT 2
- Pretrained Model HOT 2
- about using pretrain model to continue training on the other data HOT 1
- data augmentation HOT 7
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