A Data Efficient End-To-End Spoken Language Understanding Architecture

ICASSP, pp. 8519-8523, 2020.

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Abstract:

End-to-end architectures have been recently proposed for spoken language understanding (SLU) and semantic parsing. Based on a large amount of data, those models learn jointly acoustic and linguistic-sequential features. Such architectures give very good results in the context of domain, intent and slot detection, their application in a ...More

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