Howtosignalprocessing
- What is bidirectional RNN used for?
- What is the difference between RNN and bidirectional RNN?
- Is bidirectional LSTM better than unidirectional?
What is bidirectional RNN used for?
A Bidirectional RNN is a combination of two RNNs training the network in opposite directions, one from the beginning to the end of a sequence, and the other, from the end to the beginning of a sequence. It helps in analyzing the future events by not limiting the model's learning to past and present.
What is the difference between RNN and bidirectional RNN?
RNN has the limitation that it processes inputs in strict temporal order. This means current input has context of previous inputs but not the future. Bidirectional RNN ( BRNN ) duplicates the RNN processing chain so that inputs are processed in both forward and reverse time order.
Is bidirectional LSTM better than unidirectional?
The results show that the bidirectional approach slightly enhances the recognition quality over the unidirectional approach. However, the bidirectional approach spends more time during the training, which may hinder its applicability on large datasets.
