Sequential Convolutional Neural Networks for Slot Filling in Spoken Language Understanding
Table 4: Impact of including the current word with surrounding context into the CNN on the F1-score (%)
['Methods', 'F1-score']
The results revealed the strong impact of including the current word with its surrounding context into the CNN on the final F1-score. Without paying attention to the current word, the F1-score dropped significantly to 92.01%. Successively adding the current word and increasing its surrounding contexts up to three left and three right neighbour words resulted in better performance. Increasing the surrounding context to four, however, decreased F1-score. The best F1-score was obtained with three left and three right neighbour words.