2 citations · 2 across the 12 of their papers we have counts for
3 papers · 1 filter
End-to-end spoken language understanding using transformer networks and self-supervised pre-trained features
Edmilson Morais, Hong-Kwang J. Kuo, Samuel Thomas +2
Transformer networks and self-supervised pre-training have consistently delivered state-of-art results in the field of natural language processing (NLP); however, their merits in t…
Leveraging Unpaired Text Data for Training End-to-End Speech-to-Intent Systems
Yinghui Huang, Hong-Kwang Kuo, Samuel Thomas +5
Training an end-to-end (E2E) neural network speech-to-intent (S2I) system that directly extracts intents from speech requires large amounts of intent-labeled speech data, which is…
End-to-End Spoken Language Understanding Without Full Transcripts
Hong-Kwang J. Kuo, Zoltán Tüske, Samuel Thomas +7
An essential component of spoken language understanding (SLU) is slot filling: representing the meaning of a spoken utterance using semantic entity labels. In this paper, we develo…