  The field of conversational agents is growing fast and there is an increasing
need for algorithms that enhance natural interaction. In this work we show how
we achieved state of the art results in the Keyword Spotting field by adapting
and tweaking the Xception algorithm, which achieved outstanding results in
several computer vision tasks. We obtained about 96\% accuracy when classifying
audio clips belonging to 35 different categories, beating human annotation at
the most complex tasks proposed.
