We run LSTM1 to get the hidden representation {h f 1 ,h f 2 , ...,h fn } and run LSTM2 to get the hidden representation {h b 1 ,h b 2 , ...,h bn }.
the representation of the words as continuous vectors (word embedding) are proved more powerful than discrete representation (Bengio et al., 2003) (Mikolov et al., 2013b).