CUED Publications database

Spoken language understanding and interaction: machine learning for human-like conversational systems

Gašić, M and Hakkani-Tür, D and Celikyilmaz, A (2017) Spoken language understanding and interaction: machine learning for human-like conversational systems. Computer Speech and Language, 46. pp. 249-251. ISSN 0885-2308

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Abstract

© 2017 In recent years, the interest in research in speech understanding and spoken interaction has soared due to the emergence of virtual personal assistants. However, while the ability of these agents to recognise conversational speech is maturing rapidly, their ability to understand and interact is still limited. At the same time we have witnessed the development of the number of models based on machine learning that made a huge impact on spoken language understanding accuracies and the interaction quality overall. This special issue brings together a number of articles that tackle different aspects of spoken language understanding and interaction: clarifications in dialogues, adaptation to different domains, semantic tagging and error handling. These studies all have a common purpose of building human-like conversational systems.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Machine Intelligence
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:26
Last Modified: 19 Sep 2017 01:33
DOI: