Virtual assistants are becoming increasingly important speech-driven Information Retrieval
platforms that assist users with various tasks. We discuss open problems and challenges …

Virtual Assistants (VAs) are important Information Retrieval platforms that help users
accomplish various tasks through spoken commands. The speech recognition system …

The maturity of automatic speech recognition (ASR) systems at controller working positions
is currently a highly relevant technological topic in air traffic control (ATC). However, ATC …

Virtual assistants make use of automatic speech recognition (ASR) to help users answer
entity-centric queries. However, spoken entity recognition is a difficult problem, due to the …

General purpose language models (LMs) encounter difficulties when processing domain-
specific jargon and terminology, which are frequently utilized in specialized fields such as …

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 cannot …

On-device automatic speech recognition systems face several challenges compared to
server-based systems. They have to meet stricter constraints in terms of speed, disk size and …

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 …

Voice assistants increasingly use on-device Automatic Speech Recognition (ASR) to ensure
speed and privacy. However, due to resource constraints on the device, queries pertaining …

Neural language models (LM) trained on diverse corpora are known to work well on
previously seen entities, however, updating these models with dynamically changing entities …