The decoder aims to generate a story ending which accords with the target sentiment intensity s. As shown in Figure 3, the probability of generating a target word P is composed of two probabilities: where P R (y t ) denotes the semantic generation probability, P S (y t ) denotes the sentiment generation probability, ↵ and are trainable coefficients.
p R (y t ) is defined as follow: where w is a one-hot indicator vector of word w, W R and b R are trainable parameters, h t is the t-th hidden state of the LSTM decoder with attention mechanism (Luong et al., 2015).