{"id":401894,"date":"2017-07-18T14:32:42","date_gmt":"2017-07-18T21:32:42","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=401894"},"modified":"2018-10-16T20:05:37","modified_gmt":"2018-10-17T03:05:37","slug":"turn-taking-phenomena-incremental-dialogue-systems","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/turn-taking-phenomena-incremental-dialogue-systems\/","title":{"rendered":"Turn-taking phenomena in incremental dialogue systems"},"content":{"rendered":"
In this paper, a turn-taking phenomenon taxonomy is introduced, organised according to the level of information conveyed. It is aimed to provide a better grasp of the behaviours used by humans while talking to each other, so that they can be methodically replicated in spoken dialogue systems. Five interesting phenomena have been implemented in a simulated environment: the system barge-in with three variants (resulting from either an unclear, an incoherent or a sufficient user message), the feedback and the user barge-in. The experiments reported in the paper illustrate that how such phenomena are implemented is a delicate choice as their impact on the system’s performance is variable.<\/p>\n","protected":false},"excerpt":{"rendered":"
In this paper, a turn-taking phenomenon taxonomy is introduced, organised according to the level of information conveyed. It is aimed to provide a better grasp of the behaviours used by humans while talking to each other, so that they can be methodically replicated in spoken dialogue systems. Five interesting phenomena have been implemented in a […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-401894","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing 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