{"id":159894,"date":"2008-01-01T00:00:00","date_gmt":"2008-01-01T00:00:00","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/msr-research-item\/a-feature-compensation-approach-using-high-order-vector-taylor-series-approximation-of-an-explicit-distortion-model-for-noisy-speech-recognition\/"},"modified":"2018-10-16T20:00:38","modified_gmt":"2018-10-17T03:00:38","slug":"a-feature-compensation-approach-using-high-order-vector-taylor-series-approximation-of-an-explicit-distortion-model-for-noisy-speech-recognition","status":"publish","type":"msr-research-item","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/publication\/a-feature-compensation-approach-using-high-order-vector-taylor-series-approximation-of-an-explicit-distortion-model-for-noisy-speech-recognition\/","title":{"rendered":"A Feature Compensation Approach using High-Order Vector Taylor Series Approximation of An Explicit Distortion Model for Noisy Speech Recognition"},"content":{"rendered":"<div class=\"asset-content\">\n<p>This paper presents a new feature compensation approach to noisy speech recognition by using high-order vector Taylor series (HOVTS) approximation of an explicit model of environmental distortions. Formulations for maximum likelihood (ML) estimation of noise model parameters and minimum meansquared error (MMSE) estimation of clean speech are derived. Experimental results on Aurora2 database demonstrate that the proposed approach achieves consistently significant improvement in recognition accuracy compared to traditional first-order VTS based feature compensation approach.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper presents a new feature compensation approach to noisy speech recognition by using high-order vector Taylor series (HOVTS) approximation of an explicit model of environmental distortions. Formulations for maximum likelihood (ML) estimation of noise model parameters and minimum meansquared error (MMSE) estimation of clean speech are derived. Experimental results on Aurora2 database demonstrate that [&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":"jundu"},{"type":"user_nicename","value":"qianghuo"}],"msr_publishername":"International Speech Communication Association","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"Proc. of INTERSPEECH 2008","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 ISCA. 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 ISCA and\/or the author.","msr_conference_name":"Proc. of INTERSPEECH 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