{"id":480063,"date":"2018-04-16T16:55:25","date_gmt":"2018-04-16T23:55:25","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=480063"},"modified":"2018-10-16T22:27:40","modified_gmt":"2018-10-17T05:27:40","slug":"conference-paper-microsoft-2017-conversational-speech-recognition-system","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/conference-paper-microsoft-2017-conversational-speech-recognition-system\/","title":{"rendered":"The Microsoft 2017 Conversational Speech Recognition System"},"content":{"rendered":"<p>We describe the latest version of Microsoft&#8217;s conversational speech recognition system for the Switchboard and CallHome domains.\u00a0 The system adds a CNN-BLSTM acoustic model to the set of model architectures we combined previously, and includes character-based and dialog session aware LSTM language models in rescoring.\u00a0 For system combination we adopt a two-stage approach, whereby acoustic model posteriors are first combined at the senone\/frame level,followed by a word-level voting via confusion networks.\u00a0 We also added another language model rescoring step following the confusion network combination.\u00a0 The resulting system yields a 5.1% word error rate on the NIST 2000 Switchboard test set, and 9.8% on the CallHome subset.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We describe the latest version of Microsoft&#8217;s conversational speech recognition system for the Switchboard and CallHome domains.\u00a0 The system adds a CNN-BLSTM acoustic model to the set of model architectures we combined previously, and includes character-based and dialog session aware LSTM language models in rescoring.\u00a0 For system combination we adopt a two-stage approach, whereby acoustic [&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":[{"type":"user_nicename","value":"Wayne Xiong","user_id":"34811"},{"type":"user_nicename","value":"Lingfeng Wu","user_id":"32687"},{"type":"user_nicename","value":"Jasha Droppo","user_id":"32211"},{"type":"user_nicename","value":"Xuedong Huang","user_id":"34869"},{"type":"user_nicename","value":"Andreas Stolcke","user_id":"31054"}],"msr_publishername":"IEEE","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"5934-5938","msr_page_range_start":"5934","msr_page_range_end":"5938","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"Proc. 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