{"id":192717,"date":"2015-08-26T00:00:00","date_gmt":"2015-08-26T16:08:48","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/spatial-probability-for-sound-source-localization\/"},"modified":"2016-07-15T15:26:23","modified_gmt":"2016-07-15T22:26:23","slug":"spatial-probability-for-sound-source-localization","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/spatial-probability-for-sound-source-localization\/","title":{"rendered":"Spatial Probability for Sound Source Localization"},"content":{"rendered":"<div class=\"asset-content\">\n<p>In audio signal processing, sound source localization (SSL) is a mature field. This project, however, looks at the SSL problem in a slightly different perspective, in which locations are computed softly. Specifically, instead of making point-decisions about the direction of arrival (DOA) of sound sources, a belief distribution about sources&#8217; locations over frequency and DOA\/space is computed. The proposed approach generalizes the traditional SSL problem, and its outcome can also be used for other audio applications, such as spatial filtering.<\/p>\n<p>This project also investigates the SSL performance over a large set of microphone array configurations: a linear 4-element array (Kinect), a circular array with omnidirectional and cardioid microphones, and a 2-element, front-back array, with the goal of finding a &#8220;silver bullet&#8221; algorithm for all configurations. In addition to performance, computation cost is also accounted in the evaluation of different algorithms. Finally, evaluation is performed on a real data set collected at different SNR in a conference room.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In audio signal processing, sound source localization (SSL) is a mature field. This project, however, looks at the SSL problem in a slightly different perspective, in which locations are computed softly. Specifically, instead of making point-decisions about the direction of arrival (DOA) of sound sources, a belief distribution about sources&#8217; locations over frequency and DOA\/space [&hellip;]<\/p>\n","protected":false},"featured_media":199247,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_hide_image_in_river":0,"footnotes":""},"research-area":[],"msr-video-type":[206954],"msr-locale":[268875],"msr-post-option":[],"msr-session-type":[],"msr-impact-theme":[],"msr-pillar":[],"msr-episode":[],"msr-research-theme":[],"class_list":["post-192717","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-video-type-microsoft-research-talks","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/ltJle8TlfyU","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/192717","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/192717\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/199247"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=192717"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=192717"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=192717"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=192717"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=192717"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=192717"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=192717"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=192717"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=192717"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=192717"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}