Two-Pass Low Latency End-to-End Spoken Language Understanding. (arXiv:2207.06670v2 [cs.CL] UPDATED)

End-to-end (E2E) models are becoming increasingly popular for spoken language
understanding (SLU) systems and are beginning to achieve competitive
performance to pipeline-based approaches. However, recent work has shown that
these models struggle to generalize to new phrasings for the same intent
indicating that models cannot understand the semantic content of the given
utterance. In this work, we incorporated language models pre-trained on
unlabeled text data inside E2E-SLU frameworks to build strong semantic
representations. Incorporating both semantic and acoustic information can …

arxiv language spoken language understanding understanding