9 citations · 22 across the 5 of their papers we have counts for
Showing 2020 · eess.ASShow all
2 papers · 2 filters
eess.AS2020★ 8 cited
Tie Your Embeddings Down: Cross-Modal Latent Spaces for End-to-end Spoken Language Understanding
Bhuvan Agrawal, Markus Müller, Martin Radfar +3
End-to-end (E2E) spoken language understanding (SLU) systems can infer the semantics of a spoken utterance directly from an audio signal. However, training an E2E system remains a…
eess.AS2020★ 9 cited
Streaming End-to-End Bilingual ASR Systems with Joint Language Identification
Surabhi Punjabi, Harish Arsikere, Zeynab Raeesy +11
Multilingual ASR technology simplifies model training and deployment, but its accuracy is known to depend on the availability of language information at runtime. Since language ide…