{"id":398150,"date":"2017-07-07T16:27:04","date_gmt":"2017-07-07T23:27:04","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=398150"},"modified":"2018-10-16T20:02:47","modified_gmt":"2018-10-17T03:02:47","slug":"intention-based-corrective-feedback-generation-using-context-aware-model","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/intention-based-corrective-feedback-generation-using-context-aware-model\/","title":{"rendered":"Intention-based Corrective Feedback Generation using Context-aware Model"},"content":{"rendered":"<p>In order to facilitate language acquisition, when language learners speak incomprehensible utterances, a\u00a0Dialog-based Computer Assisted Language Learning (DB-CALL) system should provide matching fluent\u00a0utterances by inferring the actual learner\u2019s intention both from the utterance itself and from the dialog\u00a0context as human tutors do. We propose a hybrid inference model that allows a practical and principled way\u00a0of separating the utterance model and the dialog context model so that only the utterance model needs to be\u00a0adjusted for each fluency level. Also, we propose a feedback generation method that provides native-like\u00a0utterances by searching Example Expression Database using the inferred intention. In experiments, our\u00a0hybrid model outperformed the utterance only model. Also, from the increased dialog completion rate, we\u00a0can conclude that our method is suitable to produce appropriate feedback even when the learner&#8217;s utterances\u00a0are highly incomprehensible. This is because the dialog context model effectively confines candidate\u00a0intentions within the given context.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In order to facilitate language acquisition, when language learners speak incomprehensible utterances, a\u00a0Dialog-based Computer Assisted Language Learning (DB-CALL) system should provide matching fluent\u00a0utterances by inferring the actual learner\u2019s intention both from the utterance itself and from the dialog\u00a0context as human tutors do. We propose a hybrid inference model that allows a practical and principled way\u00a0of [&hellip;]<\/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":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"International Conference on Computer Supported Education, Valencia, Spain","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"International Conference on Computer Supported Education, Valencia, 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