Intent Detection and Slot Filling with Capsule Net Architectures for a Romanian Home Assistant

Intent Detection and Slot Filling with Capsule Net Architectures for a Romanian Home Assistant

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As virtual home assistants are becoming more popular, there is an emerging need for supporting languages other than English.While more wide-spread or hp pavilion 15-eg1053cl popular languages such as Spanish, French or Hindi are already integrated into existing home assistants like Google Home or Alexa, integration of other less-known languages such as Romanian is still missing.This paper explores the problem of Natural Language Understanding (NLU) applied to a Romanian home assistant.We propose a customized capsule acure face lotion neural network architecture that performs intent detection and slot filling in a joint manner and we evaluate how well it handles utterances containing various levels of complexity.

The capsule network model shows a significant improvement in intent detection when compared to models built using the well-known Rasa NLU tool.Through error analysis, we observe clear error patterns that occur systematically.Variability in language when expressing one intent proves to be the biggest challenge encountered by the model.