{"id":155566,"date":"2007-04-01T00:00:00","date_gmt":"2007-04-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/stationary-tones-interference-cancellation-using-adaptive-tracking\/"},"modified":"2020-06-04T15:25:01","modified_gmt":"2020-06-04T22:25:01","slug":"stationary-tones-interference-cancellation-using-adaptive-tracking","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/stationary-tones-interference-cancellation-using-adaptive-tracking\/","title":{"rendered":"Stationary-Tones Interference Cancellation Using Adaptive Tracking"},"content":{"rendered":"<div class=\"asset-content\">\n<p>It is usual in practice that recorded sounds are contaminated by stationary tones coming from power wiring (50\/60 Hz or 400 Hz and their harmonics), frame or line frequencies from a nearby TV or monitor, computer fans, hard disk drives, etc. They are mostly stationary, but their removal using a stationary noise suppressor results in notch filtering, removing the speech content at those frequencies, because the SNRs are usually low. In this paper we propose fast, real-time algorithm for removing constant tones while keeping intact the speech content. We build and adaptively update a model of the constant tones, extrapolating it for subtraction from the next frame. In our evaluations, the proposed algorithm reduces the amplitudes of such stationary tones up to 15 dB, without introducing artifacts such as nonlinear distortions or musical noises. This algorithm is applicable as pre-processor before a classic gain-based stationary oise suppressor.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>It is usual in practice that recorded sounds are contaminated by stationary tones coming from power wiring (50\/60 Hz or 400 Hz and their harmonics), frame or line frequencies from a nearby TV or monitor, computer fans, hard disk drives, etc. They are mostly stationary, but their removal using a stationary noise suppressor results in [&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":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[243062,13551],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-155566","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-audio-acoustics","msr-research-area-graphics-and-multimedia","msr-locale-en_us"],"msr_publishername":"Institute of Electrical and Electronics Engineers, Inc.","msr_edition":"","msr_affiliation":"","msr_published_date":"2007-4-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"208676","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/Tashev_Malvar_StationaryTonesCancellation.pdf","id":"208676","title":"Tashev_Malvar_StationaryTonesCancellation.pdf","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":208676,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/Tashev_Malvar_StationaryTonesCancellation.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"Ivan Tashev","user_id":32127,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Ivan Tashev"},{"type":"user_nicename","value":"Rico Malvar","user_id":32786,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Rico Malvar"}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[144923],"msr_project":[488189],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":488189,"post_title":"Sound Capture and Speech Enhancement","post_name":"sound-capture-speech-enhancement","post_type":"msr-project","post_date":"2018-06-12 09:35:37","post_modified":"2022-04-08 12:58:58","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/sound-capture-speech-enhancement\/","post_excerpt":"The goal of device design is to overcome the device, room, and noise effects, ultimately 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