Spoken Language Understanding(SLU)/Slot Filling in Keras.
There are 4 models created in Keras to solve the Airline Travel Information System(ATIS) dataset.
- Simple RNN
- LSTM
- CNN with GRUs to Capture Future Contexts
- BiDirectional LSTM
Here is an example sentence and its labels from the dataset:
Show | flights | from | Boston | to | New | York | today |
---|---|---|---|---|---|---|---|
O | O | O | B-dept | O | B-arr | I-arr | B-date |
Model | RNN | LSTM | GRU-CNN | BD-LSTM | BD-CNN* |
---|---|---|---|---|---|
F1 Score | 93.02 | 94.24 | 94.72 | 95.43 | 95.61 |
*Model Results are from Sequential Convolutional Neural Networks for Slot Filling in Spoken Language Understanding, Ngoc Thang. Vu. and hasn't been evaluated in the code.