A deep learning approach for understanding natural language commands for mobile service robots
TABLE X: Comparison of the performance in the slot filling task when varying the neural network architecture, for GPSR
['[EMPTY]', 'Accuracy']
This happens because the slot filling task corresponds to a more complex task, since it is a sequence tagging, an assignment of a categorical label to each member of the sequence, instead of a single classification. Also, the results obtained are better using bidirectional LSTMs, due to the fact that a classification of a word can depend on the following words instead of only on the previous words.