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- W4367189587 abstract "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." @default.
- W4367189587 created "2023-04-28" @default.
- W4367189587 creator A5084609544 @default.
- W4367189587 date "2023-07-18" @default.
- W4367189587 modified "2023-09-26" @default.
- W4367189587 title "Modeling Spoken Information Queries for Virtual Assistants: Open Problems, Challenges and Opportunities" @default.
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- W4367189587 doi "https://doi.org/10.1145/3539618.3591849" @default.
- W4367189587 hasPublicationYear "2023" @default.
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