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arXiv · 1907.05403

Incrementalizing RASA's Open-Source Natural Language Understanding Pipeline

Andrew Rafla·Casey Kennington
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Abstract

As spoken dialogue systems and chatbots are gaining more widespread adoption, commercial and open-sourced services for natural language understanding are emerging. In this paper, we explain how we altered the open-source RASA natural language understanding pipeline to process incrementally (i.e., word-by-word), following the incremental unit framework proposed by Schlangen and Skantze. To do so, we altered existing RASA components to process incrementally, and added an update-incremental intent recognition model as a component to RASA. Our evaluations on the Snips dataset show that our changes allow RASA to function as an effective incremental natural language understanding service.

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Andrew Rafla, Casey Kennington. 2019-07-11. Incrementalizing RASA's Open-Source Natural Language Understanding Pipeline. https://arxiv.org/abs/1907.05403

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