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Speech Commands Recognition

内容介绍

https://zhuanlan.zhihu.com/p/331833198

实验结果

Local CV Score Test Score
0.977 ± 0.001​ 0.975 ± 0.001

本方案基于pytorch和keras4torch。为方便移植到其他框架测试,下面列出了训练用到的主要设定。

主要设定

setting value
features 1x32x32 melspectrogram
model wide resnet28
total parameters 36491726
epochs 40
batch size 96
optimizer SGD with momentum
learning rate 1e-2 -> 3e-3 -> 9e-4 -> 8e-5
L2 regularization 1e-2
label smoothing 0.1
epoch time 82s (1 * RTX 2080Ti)

模型结构

运行仓库代码

环境配置

torch>=1.6.0
keras4torch==1.1.3
scikit-learn==0.23.2

librosa==0.8.0

如果使用linux系统,需要先执行如下命令才能安装librosa。

! sudo apt-get install -y libsndfile1

数据预处理

确保原始数据被放在data/ 文件夹中,运行preprocess.ipynb。

这些文件的结构如下:

  • data/
    • train/
    • test/
  • preprocess.ipynb
  • train.ipynb

训练和预测

在上一步完成的基础上,运行train.ipynb。

结束后,对测试集的预测(概率值)将被保存为一个.npy文件。

问题反馈

speech_commands_recognition's People

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