A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf
.
A Study into Pre-training Strategies for Spoken Language Understanding on Dysarthric Speech
[article]
2021
arXiv
pre-print
End-to-end (E2E) spoken language understanding (SLU) systems avoid an intermediate textual representation by mapping speech directly into intents with slot values. This approach requires considerable domain-specific training data. In low-resource scenarios this is a major concern, e.g., in the present study dealing with SLU for dysarthric speech. Pretraining part of the SLU model for automatic speech recognition targets helps but no research has shown to which extent SLU on dysarthric speech
arXiv:2106.08313v1
fatcat:6rvmm7swvvcc7ij6osh7dtnbfi