Practical Guidelines for Intent Recognition: BERT with Minimal Training Data Evaluated in Real-World HRI Application

Intent recognition models, which match a written or spoken input's class in order to guide an interaction, are an essential part of modern voice user interfaces, chatbots, and social robots. However, getting enough data to train these models can be very expensive and challenging, especially whe...

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Veröffentlicht in:	2021 16th ACM/IEEE International Conference on Human-Robot Interaction (HRI) S. 341 - 350
Hauptverfasser:	Huggins, Matthew, Alghowinem, Sharifa, Jeong, Sooyeon, Colon-Hernandez, Pedro, Breazeal, Cynthia, Park, Hae Won
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	ACM 09.03.2021
Schlagworte:	BERT Bit error rate Codes Computational modeling Data models intent recognition natural language processing real-world HRI application Social robots Training Training data
ISSN:	2167-2148
Online-Zugang:	Volltext
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