A Multi-Task Hierarchical Approach for Intent Detection and Slot Filling
Abstract
Spoken language understanding (SLU) plays an integral part in every dialogue system. To understand the intention of the user and extract the necessary information to help the user achieve desired goals is a challenging task. In this work, we propose an end-to-end hierarchical multi-task model that can jointly perform both intent detection and slot filling tasks for the datasets of varying domains. The primary aim is to capture context...
Paper Details
Title
A Multi-Task Hierarchical Approach for Intent Detection and Slot Filling
Published Date
Nov 1, 2019
Journal
Volume
183
Pages
104846 - 104846
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