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Our work introduces the first interruptibility-aware mobile-robot system, which uses social and contextual cues online to accurately determine when to interrupt a person. We evaluate multiple non-temporal and temporal models on the interruptibility classification task, and show that a variant of Conditional Random Fields (CRFs), the Latent-Dynamic CRF, is the most robust, accurate, and appropriate model for use on our system. Additionally, we evaluate different classification features and show that the observed demeanor of a person can help in interruptibility classification; but in the presence of detection noise, robust detection of object labels as a visual cue to the interruption context can improve interruptibility estimates. Finally, we deploy our system in a large-scale user study to understand the effects of interruptibility-awareness on human-task performance, robot-task performance, and on human interpretation of the robot\u2019s social aptitude. Our results show that while participants are able to maintain task performance, even in the presence of interruptions, interruptibility-awareness improves the robot\u2019s task performance and improves participant social perceptions of the robot.<\/jats:p>","DOI":"10.1145\/3277902","type":"journal-article","created":{"date-parts":[[2019,5,7]],"date-time":"2019-05-07T12:15:57Z","timestamp":1557231357000},"page":"1-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Robot Classification of Human Interruptibility and a Study of Its Effects"],"prefix":"10.1145","volume":"7","author":[{"given":"Siddhartha","family":"Banerjee","sequence":"first","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Silva","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sonia","family":"Chernova","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2018,10,24]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/985692.985727"},{"key":"e_1_2_1_2_1","first-page":"1","article-title":"Memory for goals: An activation-based model","volume":"26","author":"Altmann Erik M.","year":"2002","journal-title":"Cognitive Science"},{"key":"e_1_2_1_3_1","volume-title":"Int. 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