This disclosure describes techniques for performing adaptive summarization of responses provided by a digital assistant to a user’s queries based on explicit and/or implicit feedback from the user that is indicative of their engagement with given responses. The feedback is determined based on user-permitted data from device sensors. If the user permits, past reactions of the user to output responses are used to train machine learning models or heuristics/rules that are used to determine the length of a query response appropriate for the user. Described features enable a digital assistant to automatically match the response length (duration) to the user’s query type, context, and preferences. This enables the digital assistant to provide an engaging interaction experience, since the user is unlikely to need to interrupt responses or disengage from the digital assistant midway through a response.
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Sharifi, Matthew and Carbune, Victor, "Adaptive Summarization of Digital Assistant Responses to User Queries", Technical Disclosure Commons, (November 24, 2020)