We split the task of semantic decoding into two steps: (i) training a joint model for predicting the dialogue act and presence or absence of slots and (ii) predicting the values for the most probable slots detected in (i).
when evaluating on the DSTC2 test set, a window of 4 (w4), performs slightly better than other window sizes and better than the simple CNN model.