Spoken Language Understanding on the Edge
  We consider the problem of performing Spoken Language Understanding (SLU) on
small devices typical of IoT applications. Our contributions are twofold.
First, we outline the design of an embedded, private-by-design SLU system and
show that it has performance on par with cloud-based commercial solutions.
Second, we release the datasets used in our experiments in the interest of
reproducibility and in the hope that they can prove useful to the SLU
community.
