Comments (4)
什么问题?
What is your problem?
from speech-emotion-recognition.
您好,我在重现代码的时候报错,在定义X维度:X = tf.placeholder(tf.float32, shape=[None, 200, 40, 3])维度这里出错,修改之后,验证集的准确率在53%左右,而不是论文中的64%左右,我想问是因为在代码中没有加入attention机制的原因吗,我看attention那段代码注释掉了,谢谢回复。
from speech-emotion-recognition.
64%是10交叉验证后的平均值,对于不同的验证集和测试集,你会发现效果相差很大,高的有70%多,差的50%几,而且你解决了样本不均衡问题吗?有问题可以给我写邮件[email protected],这样回复可能比较及时
from speech-emotion-recognition.
好的,谢谢
from speech-emotion-recognition.
Related Issues (20)
- how train with EmoBD (7 emotion)
- Incompatible shapes: [654] vs. [436] HOT 1
- 关于utils.py测试的问题 HOT 7
- 数据处理部分 HOT 1
- 对代码的几点疑惑 HOT 1
- train loss 下降,但valid loss 有下小降,然后大幅上升
- train loss 下降,但valid loss 有下小降,然后大幅上升 HOT 1
- 数据集的处理问题 HOT 5
- 关于特征提取问题 HOT 1
- 关于one_hot编码 HOT 3
- 关于utils.py,关于berlin库 HOT 2
- Did not found the IEMOCAP DATASET
- 一些文件没有用到
- No module named 'python_speech_features
- IndexError: index 4833 is out of bounds for size 4800 HOT 1
- Can you provide Checkpoint, please HOT 1
- How to use 'Happy' data twice HOT 1
- How to use model1.py? HOT 1
- 进行模型评估的时候报错 key cnn/unit-1/bn1/beta not found,求解答,谢谢 HOT 1
- KeyError: 'wav\\Ses01F_impro01\\Ses01F_impro01_F000'
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from speech-emotion-recognition.