In this article, reinforcement learning is used to learn an optimal turn-taking strategy for vocal human-machine dialogue. The Orange Labs’ Ma-jordomo dialogue system, which allows the users to have conversations within a smart home, has been upgraded to an incremental version. First, a user simulator is built in order to generate a dialogue corpus which thereafter is used to optimise the turn-taking strategy from delayed rewards with the Fitted-Q reinforcement learning algorithm. Real users test and evaluate the new learnt strategy, versus a non-incremental and a handcrafted incremen-tal strategies. The data-driven strategy is shown to significantly improve the task completion ratio and to be preferred by the users according to subjective metrics.<\/p>\n","protected":false},"excerpt":{"rendered":"
In this article, reinforcement learning is used to learn an optimal turn-taking strategy for vocal human-machine dialogue. The Orange Labs’ Ma-jordomo dialogue system, which allows the users to have conversations within a smart home, has been upgraded to an incremental version. First, a user simulator is built in order to generate a dialogue corpus which […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"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-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-401912","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 25th International Joint Conference on Artificial Intelligence 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