The paper provides an overview of the \u201cMulti-domain Task Completion\u201d track (Track 1) at the 8th Dialog System Technology Challenge (DSTC-8). There are two tasks in this track. The first task is end-to-end multi-domain task-completion, which aims to build end-to-end task completion dialog systems based on ConvLab. The second task is fast domain adaptation, seeking to develop models that predict user responses when only limited in-domain data is available. We describe the submissions for both tasks, automatic evaluation and human evaluation procedures, and discuss the outcomes of these two evaluations.<\/p>\n","protected":false},"excerpt":{"rendered":"
The paper provides an overview of the \u201cMulti-domain Task Completion\u201d track (Track 1) at the 8th Dialog System Technology Challenge (DSTC-8). There are two tasks in this track. The first task is end-to-end multi-domain task-completion, which aims to build end-to-end task completion dialog systems based on ConvLab. The second task is fast domain adaptation, seeking […]<\/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":[13556,13545,13554],"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-645273","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-human-language-technologies","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2020-2-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/03\/DSTC8.pdf","id":"645279","title":"dstc8","label_id":"243132","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":645279,"url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/03\/DSTC8.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"Jinchao Li","user_id":38826,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Jinchao Li"},{"type":"user_nicename","value":"Baolin Peng","user_id":38835,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Baolin Peng"},{"type":"user_nicename","value":"Sungjin Lee","user_id":36377,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Sungjin Lee"},{"type":"user_nicename","value":"Jianfeng Gao","user_id":32246,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Jianfeng Gao"},{"type":"text","value":"Ryuichi Takanobu","user_id":0,"rest_url":false},{"type":"text","value":"Qi Zhu","user_id":0,"rest_url":false},{"type":"edited_text","value":"Minlie Huang","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Hannes Schulz","user_id":37188,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Hannes Schulz"},{"type":"user_nicename","value":"Adam Atkinson","user_id":37095,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Adam Atkinson"},{"type":"user_nicename","value":"Mahmoud Adada","user_id":37176,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Mahmoud Adada"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[144931,390593],"msr_project":[569514],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":569514,"post_title":"Multi-Domain Task-Completion Dialog Challenge","post_name":"multi-domain-task-completion-dialog-challenge","post_type":"msr-project","post_date":"2019-02-24 10:44:56","post_modified":"2019-06-17 13:49:02","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/multi-domain-task-completion-dialog-challenge\/","post_excerpt":"As part of the Eighth Dialog System Technology Challenge (DSTC8), Microsoft Research and Tsinghua University are hosting a track intended to foster progress in two important aspects of dialog systems: dialog complexity and scaling to new domains. 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