  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 to forecast which entities will gain in
popularity and become trending, and it subsequently integrates the predictions
within the Automated Speech Recognition (ASR) component of the VA. Experiments
show that our proposed approach results in a 20% relative reduction in errors
on emerging entity name utterances without degrading the overall recognition
quality of the system.
