  Virtual assistants are becoming increasingly important speech-driven
Information Retrieval platforms that assist users with various tasks.
  We discuss open problems and challenges with respect to modeling spoken
information queries for virtual assistants, and list opportunities where
Information Retrieval methods and research can be applied to improve the
quality of virtual assistant speech recognition.
  We discuss how query domain classification, knowledge graphs and user
interaction data, and query personalization can be helpful to improve the
accurate recognition of spoken information domain queries. Finally, we also
provide a brief overview of current problems and challenges in speech
recognition.
