Multi-Domain Spoken Language Understanding Using Domain- and Task-Aware Parameterization

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Abstract:

Spoken language understanding has been addressed as a supervised learning problem, where a set of training data is available for each domain. However, annotating data for each domain is both financially costly and non-scalable so we should fully utilize information across all domains. One existing approach solves the problem by conducti...More

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