{"id":156647,"date":"2008-05-01T00:00:00","date_gmt":"2008-05-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/bridging-the-gap-towards-a-unified-framework-for-hands-free-speech-recognition-using-microphone-arrays\/"},"modified":"2018-10-16T21:01:19","modified_gmt":"2018-10-17T04:01:19","slug":"bridging-the-gap-towards-a-unified-framework-for-hands-free-speech-recognition-using-microphone-arrays","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/bridging-the-gap-towards-a-unified-framework-for-hands-free-speech-recognition-using-microphone-arrays\/","title":{"rendered":"Bridging the gap: towards a unified framework for hands-free speech recognition using microphone arrays"},"content":{"rendered":"<div class=\"asset-content\">\n<p>In this paper we describe two families of algorithms for hands-free speech recognition using microphone arrays. Enhancement-based approaches use a cascade of independent processing blocks to perform speech enhancement followed by speech recognition. We discuss the reasons why this approach may be sub-optimal and motivate the need for a solution that tightly integrates all processing blocks into a common unified framework. This leads to a second family of algorithms called unified approaches which considers all processing stages to be components of a single system that operates with the common goal of improved recognition accuracy. We describe several examples of such algorithms that have been shown to outperform more traditional signal-processing-based approaches. In doing so, we hope to convey the benefits of performing hands-free speech recognition in this manner and motivate further research in this area.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper we describe two families of algorithms for hands-free speech recognition using microphone arrays. Enhancement-based approaches use a cascade of independent processing blocks to perform speech enhancement followed by speech recognition. We discuss the reasons why this approach may be sub-optimal and motivate the need for a solution that tightly integrates all processing [&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":"mseltzer"}],"msr_publishername":"Institute of Electrical and Electronics Engineers, Inc.","msr_publisher_other":"","msr_booktitle":"Proceedings of the Workshop on Hands-Free Speech Communication and Microphone Arrays","msr_chapter":"","msr_edition":"Proceedings of the Workshop on Hands-Free Speech Communication and Microphone Arrays","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":"\u00a9 2007 IEEE. Personal use of this material is permitted. However, permission to reprint\/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.","msr_conference_name":"Proceedings of the Workshop on Hands-Free Speech Communication and Microphone Arrays","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Michael L. 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So, why has senior researcher Li Deng been trying to get rid of close-talking microphones? Close-talking microphones pick up relatively little background noise and speech recognition systems can obtain decent accuracy with them. 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