An end-to-end SLU architecture with frozen SSL acoustic encoder, LSTM classification head, and cross-modal distillation achieves 93% accuracy on simple commands and 82% on spontaneous speech at 7 ms latency on the new VoiceStick corpus, outperforming cascade baselines.
Speech-language Pre-training for End-to-end Spoken Language Un- derstanding,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.AS 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
End-to-End Voice Intent Recognition for Spontaneous Human-Drone Interaction with Naive Users
An end-to-end SLU architecture with frozen SSL acoustic encoder, LSTM classification head, and cross-modal distillation achieves 93% accuracy on simple commands and 82% on spontaneous speech at 7 ms latency on the new VoiceStick corpus, outperforming cascade baselines.