{"id":181958,"date":"2009-07-02T00:00:00","date_gmt":"2009-10-31T09:14:27","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/a-spoken-language-interpretation-component-for-a-robot-dialogue-system\/"},"modified":"2016-09-09T09:52:01","modified_gmt":"2016-09-09T16:52:01","slug":"a-spoken-language-interpretation-component-for-a-robot-dialogue-system","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/a-spoken-language-interpretation-component-for-a-robot-dialogue-system\/","title":{"rendered":"A Spoken Language Interpretation Component for a Robot Dialogue System"},"content":{"rendered":"<div class=\"asset-content\">\n<p>The DORIS project aims to develop a spoken dialogue module for an autonomous robotic agent. In this talk, I will examine the techniques used by Scusi?, the speech interpretation component of DORIS, to postulate and assess hypotheses regarding the meaning of a spoken utterance, including our formalism for disambiguating referring expressions. I will also present the results of our evaluation experiments, and discuss our progress towards the interpretation of multiple utterances.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The DORIS project aims to develop a spoken dialogue module for an autonomous robotic agent. In this talk, I will examine the techniques used by Scusi?, the speech interpretation component of DORIS, to postulate and assess hypotheses regarding the meaning of a spoken utterance, including our formalism for disambiguating referring expressions. I will also present [&hellip;]<\/p>\n","protected":false},"featured_media":194384,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"research-area":[],"msr-video-type":[],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-181958","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/LIQS-KCWSBw","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/181958"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/181958\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/194384"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=181958"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=181958"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=181958"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=181958"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=181958"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=181958"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}