Learning concepts through conversations in spoken dialogue systems
Robin Jia, Larry P. Heck, Dilek Hakkani-Tür, Georgi Nikolov
Abstract
Spoken dialogue systems must be able to recover gracefully from unexpected user inputs. In many cases, these unexpected utterances may be within the scope of the system, but include previously unseen phrases that the system cannot interpret. In this work, we augment a spoken dialogue system with the ability to learn about new concepts by conversing with the user in natural language. We present a novel model that detects phrases corresponding to such concepts, using information from a neural slotfiller as well as syntactic cues. The system then prompts the user for a definition of the detected phrases, and uses these definitions to re-parse the original utterance. We demonstrate significant gains by learning from the user, compared to a baseline system.
BibTeX
@inproceedings{icassp2017_learningconcepts,
title = {Learning concepts through conversations in spoken dialogue systems},
author = {Robin Jia and Larry P. Heck and Dilek Hakkani-Tür and Georgi Nikolov},
booktitle = {ICASSP 2017},
year = {2017}
}