Table 4 Performance of the proposed systems on the test set
From: Neural network-based non-intrusive speech quality assessment using attention pooling function
Stytems | R | RMSE |
|---|---|---|
LSTM-max | 0.961 | 0.283 |
LSTM-avgerage | 0.953 | 0.365 |
LSTM-linear softmax | 0.949 | 0.335 |
LSTM-attention | 0.962 | 0.283 |
CNN-max | 0.955 | 0.302 |
CNN-avgerage | 0.959 | 0.370 |
CNN-linear softmax | 0.961 | 0.317 |
CNN-attention | 0.963 | 0.299 |
CNN-LSTM-max | 0.964 | 0.273 |
CNN-LSTM-avgerage | 0.965 | 0.283 |
CNN-LSTM-linear softmax | 0.957 | 0.315 |
CNN-LSTM-attention | 0.967 | 0.269 |