activity
20172021
most citedTie Your Embeddings Down: Cross-Modal Latent Spaces for End-to-end Spoken Language Understanding

8 citations · 8 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2021

End-to-End Spoken Language Understanding for Generalized Voice Assistants

Michael Saxon, Samridhi Choudhary, Joseph P. McKenna +1

End-to-end (E2E) spoken language understanding (SLU) systems predict utterance semantics directly from speech using a single model. Previous work in this area has focused on target…

cs.CL2020

Extreme Model Compression for On-device Natural Language Understanding

Kanthashree Mysore Sathyendra, Samridhi Choudhary, Leah Nicolich-Henkin

In this paper, we propose and experiment with techniques for extreme compression of neural natural language understanding (NLU) models, making them suitable for execution on resour…

eess.AS20208 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…

cs.CL2020

Semantic Complexity in End-to-End Spoken Language Understanding

Joseph P. McKenna, Samridhi Choudhary, Michael Saxon +2

End-to-end spoken language understanding (SLU) models are a class of model architectures that predict semantics directly from speech. Because of their input and output types, we re…

cs.CL2017

Linguistic Markers of Influence in Informal Interactions

Shrimai Prabhumoye, Samridhi Choudhary, Evangelia Spiliopoulou +3

There has been a long standing interest in understanding `Social Influence' both in Social Sciences and in Computational Linguistics. In this paper, we present a novel approach to…