{"id":507317,"date":"2018-09-24T22:42:31","date_gmt":"2018-09-25T05:42:31","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=507317"},"modified":"2019-05-08T23:45:48","modified_gmt":"2019-05-09T06:45:48","slug":"blind-reverberation-time-estimation-using-a-convolutional-neural-network","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/blind-reverberation-time-estimation-using-a-convolutional-neural-network\/","title":{"rendered":"Blind reverberation time estimation using a convolutional neural network"},"content":{"rendered":"

The reverberation time of an acoustic environment is a useful parameter for applications including source localisation, speech recognition and mixed reality. However, estimating the reverberation time blindly and on the fly remains a challenge. Here we propose formulating the estimation as a regression problem and using a convolutional neural network (CNN) to estimate the reverberation time directly from a four second long single-channel recording of reverberant speech in noise. Evaluation on the ACE Challenge data corpus suggests that the proposed method is computationally efficient and outperforms state-of-the-art methods.<\/p>\n

\"CNN

Block diagram of convolutional neural network architecture<\/p><\/div>\n

\"T60

Confusion matrices of ground truth and estimated T60 for training set (left) and evaluation set (right). Results are binned by T60 with a resolution of 0.1 s.<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

The reverberation time of an acoustic environment is a useful parameter for applications including source localisation, speech recognition and mixed reality. However, estimating the reverberation time blindly and on the fly remains a challenge. Here we propose formulating the estimation as a regression problem and using a convolutional neural network (CNN) to estimate the reverberation […]<\/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":"Hannes Gamper","user_id":"31943"},{"type":"user_nicename","value":"Ivan Tashev","user_id":"32127"}],"msr_publishername":"IEEE","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"1","msr_page_range_end":"5","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"Proc. International Workshop on Acoustic Signal Enhancement (IWAENC)","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"","msr_other_contributors":"","msr_speaker":"","msr_award":"Nominated for best paper award","msr_affiliation":"","msr_institution":"","msr_host":"","msr_version":"","msr_duration":"","msr_original_fields_of_study":"","msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2018-9-18","msr_highlight_text":"","msr_notes":"Nominated for best paper award","msr_longbiography":"","msr_publicationurl":"","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":0,"msr_citation_count":0,"msr_influential_citations":0,"msr_reference_count":0,"msr_s2_match_confidence":0,"msr_microsoftintellectualproperty":true,"msr_s2_open_access":false,"msr_s2_author_ids":[],"msr_pub_ids":[],"msr_hide_image_in_river":0,"footnotes":""},"msr-research-highlight":[],"research-area":[13561,13556,243062],"msr-publication-type":[193716],"msr-publisher":[],"msr-focus-area":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-507317","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-algorithms","msr-research-area-artificial-intelligence","msr-research-area-audio-acoustics","msr-locale-en_us"],"msr_publishername":"IEEE","msr_edition":"","msr_affiliation":"","msr_published_date":"2018-9-18","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":"Nominated for best paper award","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":"507320","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2018\/09\/Blind_reverberation_time_estimation_Gamper_IWAENC_2018.pdf","id":"507320","title":"Blind_reverberation_time_estimation_Gamper_IWAENC_2018","label_id":"243132","label":0}],"msr_related_uploader":"","msr_citation_count":0,"msr_citation_count_updated":"","msr_s2_paper_id":"","msr_influential_citations":0,"msr_reference_count":0,"msr_arxiv_id":"","msr_s2_author_ids":[],"msr_s2_open_access":false,"msr_s2_pdf_url":null,"msr_attachments":[],"msr-author-ordering":[{"type":"user_nicename","value":"Hannes Gamper","user_id":31943,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Hannes Gamper"},{"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"}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[144923],"msr_project":[212079],"publication":[],"video":[],"msr-tool":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":212079,"post_title":"Spatial Audio","post_name":"spatial-audio","post_type":"msr-project","post_date":"2015-12-01 18:14:03","post_modified":"2022-01-21 12:44:12","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/spatial-audio\/","post_excerpt":"Spatial audio, also known as 3D stereo sound, is about creating a 3D audio experience by using headphones. 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