7 citations · 7 across the 2 of their papers we have counts for
3 papers
Using Pause Information for More Accurate Entity Recognition
Sahas Dendukuri, Pooja Chitkara, Joel Ruben Antony Moniz +3
Entity tags in human-machine dialog are integral to natural language understanding (NLU) tasks in conversational assistants. However, current systems struggle to accurately parse s…
Error-driven Pruning of Language Models for Virtual Assistants
Sashank Gondala, Lyan Verwimp, Ernest Pusateri +2
Language models (LMs) for virtual assistants (VAs) are typically trained on large amounts of data, resulting in prohibitively large models which require excessive memory and/or can…
Predicting Entity Popularity to Improve Spoken Entity Recognition by Virtual Assistants
Christophe Van Gysel, Manos Tsagkias, Ernest Pusateri +1
We focus on improving the effectiveness of a Virtual Assistant (VA) in recognizing emerging entities in spoken queries. We introduce a method that uses historical user interactions…