{"id":154782,"date":"2006-01-01T00:00:00","date_gmt":"2006-01-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/rapid-development-of-spoken-language-understanding-grammars\/"},"modified":"2018-10-16T20:16:48","modified_gmt":"2018-10-17T03:16:48","slug":"rapid-development-of-spoken-language-understanding-grammars","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/rapid-development-of-spoken-language-understanding-grammars\/","title":{"rendered":"Rapid Development of Spoken Language Understanding Grammars"},"content":{"rendered":"<div class=\"asset-content\">\n<p>To facilitate the development of spoken dialog systems and speech enabled applications, we introduce SGStudio (Semantic Grammar Studio), a grammar authoring tool that enables regular software developers with little speech\/linguistic background to rapidly create quality semantic grammars for automatic speech recognition (ASR) and spoken language understanding (SLU). We focus on the underlying technology of SGStudio, including knowledge assisted example-based grammar learning, grammar controls and configurable grammar structures. While the focus of SGStudio is to increase productivity, experimental results show that it also improves the quality of the grammars being developed.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>To facilitate the development of spoken dialog systems and speech enabled applications, we introduce SGStudio (Semantic Grammar Studio), a grammar authoring tool that enables regular software developers with little speech\/linguistic background to rapidly create quality semantic grammars for automatic speech recognition (ASR) and spoken language understanding (SLU). We focus on the underlying technology of SGStudio, [&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":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13545],"msr-publication-type":[193715],"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-154782","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-language-technologies","msr-locale-en_us"],"msr_publishername":"Elsevier","msr_edition":"","msr_affiliation":"","msr_published_date":"2006-01-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"390-416","msr_chapter":"","msr_isbn":"","msr_journal":"Speech Communication","msr_volume":"48","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"3-4","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":"229600","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"2006-wang-acero-speechcom.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2006\/01\/2006-wang-acero-speechcom.pdf","id":229600,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":229600,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2006\/01\/2006-wang-acero-speechcom.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"yeyiwang","user_id":34993,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=yeyiwang"},{"type":"user_nicename","value":"alexac","user_id":30932,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=alexac"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[171150,170147,169461],"publication":[],"video":[],"download":[],"msr_publication_type":"article","related_content":{"projects":[{"ID":171150,"post_title":"Spoken Language Understanding","post_name":"spoken-language-understanding","post_type":"msr-project","post_date":"2013-05-01 11:46:32","post_modified":"2019-08-19 14:48:51","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/spoken-language-understanding\/","post_excerpt":"Spoken language understanding (SLU) is an emerging field in between the areas of speech processing and natural language processing. The term spoken language understanding has largely been coined for targeted understanding of human speech directed at machines. This project covers our research on SLU tasks such as domain detection, intent determination, and slot filling, using data-driven methods. Projects Deeper Understanding: Moving\u00a0beyond shallow targeted understanding towards building domain independent SLU models. Scaling SLU: Quickly bootstrapping SLU&hellip;","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171150"}]}},{"ID":170147,"post_title":"Understand User's Intent from Speech and Text","post_name":"understand-users-intent-from-speech-and-text","post_type":"msr-project","post_date":"2008-12-17 11:20:26","post_modified":"2019-08-19 15:33:37","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/understand-users-intent-from-speech-and-text\/","post_excerpt":"Understanding what users like to do\/need to get is critical in human computer interaction. When natural user interface like speech or natural language is used in human-computer interaction, such as in a spoken dialogue system or with an internet search engine, language understanding becomes an important issue. Intent understanding is about identifying the action a user wants a computer to take or the information she\/he would like to obtain, conveyed in a spoken utterance or&hellip;","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170147"}]}},{"ID":169461,"post_title":"Automatic Grammar Induction","post_name":"automatic-grammar-induction","post_type":"msr-project","post_date":"2002-02-19 14:32:24","post_modified":"2019-08-14 14:41:22","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/automatic-grammar-induction\/","post_excerpt":"Automatic learning of speech recognition grammars from example sentences to ease the development of spoken language systems. Researcher Ye-Yi Wang wants to have more time for vacation, so he is teaching his computer to do some work for him. Wang has been working on Spoken Language Understanding for the MiPad project since he was hired to Microsoft Research. He has developed a robust parser and the understanding grammars for several projects. \"Grammar development is painful&hellip;","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/169461"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/154782"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/154782\/revisions"}],"predecessor-version":[{"id":525427,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/154782\/revisions\/525427"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=154782"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=154782"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=154782"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=154782"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=154782"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=154782"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=154782"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=154782"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=154782"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=154782"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=154782"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=154782"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=154782"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=154782"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=154782"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=154782"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}