{"id":156478,"date":"1990-04-01T00:00:00","date_gmt":"1990-04-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/environmental-robustness-in-automatic-speech-recognition\/"},"modified":"2018-10-16T20:35:46","modified_gmt":"2018-10-17T03:35:46","slug":"environmental-robustness-in-automatic-speech-recognition","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/environmental-robustness-in-automatic-speech-recognition\/","title":{"rendered":"Environmental Robustness in Automatic Speech Recognition"},"content":{"rendered":"<div class=\"asset-content\">\n<p>In this paper we report our initial efforts to make SPHINX, the CMU continuous-speech speaker-independent recognition system, robust to changes in the environment. To deal with differences in noise level and spectral tilt between close-talking and desktop microphones, we propose two novel methods based on additive corrections in the cepstral domain. In the first algorithm, the additive correction depends on the instantaneous SNR of the signal. In the second technique, EM techniques are used to best match the cepstral vectors of the input utterances to the ensemble of codebook entries representing a standard acoustical ambience. Use of the proposed algorithms dramatically improves recognition accuracy when the system is tested on a microphone other than the one on which it was trained.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper we report our initial efforts to make SPHINX, the CMU continuous-speech speaker-independent recognition system, robust to changes in the environment. To deal with differences in noise level and spectral tilt between close-talking and desktop microphones, we propose two novel methods based on additive corrections in the cepstral domain. In the first algorithm, [&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":"alexac"}],"msr_publishername":"Institute of Electrical and Electronics Engineers, Inc.","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"Proc. of International Conference on Acoustics, Speech, and Signal Processing","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":"Proc. of International Conference on Acoustics, Speech, and Signal 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