514 citations · 1.4k across the 79 of their papers we have counts for
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Using Speech Synthesis to Train End-to-End Spoken Language Understanding Models
Loren Lugosch, Brett Meyer, Derek Nowrouzezahrai +1
End-to-end models are an attractive new approach to spoken language understanding (SLU) in which the meaning of an utterance is inferred directly from the raw audio without employi…
Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks
Santiago Pascual, Mirco Ravanelli, Joan Serrà +2
Learning good representations without supervision is still an open issue in machine learning, and is particularly challenging for speech signals, which are often characterized by l…
Speech Model Pre-training for End-to-End Spoken Language Understanding
Loren Lugosch, Mirco Ravanelli, Patrick Ignoto +2
Whereas conventional spoken language understanding (SLU) systems map speech to text, and then text to intent, end-to-end SLU systems map speech directly to intent through a single…