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Smart devices have become common place in many homes, and these devices canbe utilized to provide support for people with mental or physical deficits.Voice-controlled assistants are a class of smart device that collect a largeamount of data in the home. In this work we present Echo SCraper and ClAssifierof Persons (ESCAPE), an open source software for the extraction of Amazon Echointeraction data, and speaker recognition on that data. We show that ESCAPE isable to extract data from a voice-controlled assistant and classify withaccuracy who is talking, based on a small number of labeled audio data. UsingESCAPE to extract interactions recorded over 3 months in the first author'shome yields a rich dataset of transcribed audio recordings. Our resultsdemonstrate that using this software the Amazon Echo can be used to studyparticipants in a naturalistic setting with minimal intrusion. We also discussthe potential for usage of voice-controlled devices together with ESCAPE tounderstand how diseases affect individuals, and how these data can be used tomonitor disease processes in general.

ESCAPE - Echo SCraper and ClAssifier of PErsons: A novel tool to facilitate using voice-controlled devices for research