{"id":398933,"date":"2017-07-11T11:54:38","date_gmt":"2017-07-11T18:54:38","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=398933"},"modified":"2018-10-16T20:03:31","modified_gmt":"2018-10-17T03:03:31","slug":"improved-hidden-markov-modeling-speaker-independent-continuous-speech-recognition","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/improved-hidden-markov-modeling-speaker-independent-continuous-speech-recognition\/","title":{"rendered":"Improved hidden Markov modeling for speaker-independent continuous speech recognition"},"content":{"rendered":"<div class=\"container-fluid body-content\">\n<article class=\"author-page\" data-bind=\"page: {\n         id: 'detail',\n         sourceCache: true,\n         sourceOnShow: 'app\/pages\/detail.cshtml',\n         params: { id: '' }\n     }\"><\/p>\n<div class=\"id-wrapper\" data-bind=\"page: { id: '?', beforeShow: detailPage.beforeDetailPageShown, params: ['jump'] }\">\n<div class=\"pure-g container entity-detail profile-page\">\n<article class=\"container profile-page detail\">\n<section class=\"left-right-comp detail-top\">\n<div class=\"profile-card card paper\">\n<div class=\"pure-g\">\n<div class=\"pure-u-1 pure-u-md-7-8 profile-content\">\n<div>\n<section class=\"paper-abstract\" data-bind=\"with: data.abstract\">\n<p data-bind=\"text: $data\">The paper reports recent efforts to further improve the performance of the Sphinx system for speaker-independent continuous speech recognition. The recognition error rate is significantly reduced with incorporation of additional dynamic features, semi-continuous hidden Markov models, and speaker clustering. For the June 1990 (RM2) evaluation test set, the error rates of our current system are 4.3% and 19.9% for word-pair grammar and no grammar respectively.<\/p>\n<\/section>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n<\/article>\n<\/div>\n<\/div>\n<\/article>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>The paper reports recent efforts to further improve the performance of the Sphinx system for speaker-independent continuous speech recognition. The recognition error rate is significantly reduced with incorporation of additional dynamic features, semi-continuous hidden Markov models, and speaker clustering. For the June 1990 (RM2) evaluation test set, the error rates of our current system are [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13545],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-398933","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-language-technologies","msr-locale-en_us"],"msr_publishername":"","msr_edition":"HLT '90 Proceedings of the workshop on Speech and Natural 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