{"id":336623,"date":"2016-12-14T15:24:41","date_gmt":"2016-12-14T23:24:41","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&#038;p=336623"},"modified":"2020-03-13T08:13:02","modified_gmt":"2020-03-13T15:13:02","slug":"who-is-talking-to-you-witty","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/who-is-talking-to-you-witty\/","title":{"rendered":"Who Is Talking To You (WITTY)"},"content":{"rendered":"<p><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-336659 alignright\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2016\/12\/WITTY.jpg\" alt=\"witty\" width=\"300\" height=\"128\" \/><\/p>\n<h2>Mission Statement<\/h2>\n<p><em>Exploit multi-sensory information to improve user experience in\u00a0<\/em><\/p>\n<p><span style=\"margin: 0px; line-height: 107%; font-family: 'Calibri',sans-serif; font-size: 11pt;\"><span style=\"color: #000000;\">\u2022<\/span><\/span>\u00a0 Speech-centric human computer interaction<br \/>\n<span style=\"margin: 0px; line-height: 107%; font-family: 'Calibri',sans-serif; font-size: 11pt;\"><span style=\"color: #000000;\">\u2022<\/span><\/span>\u00a0 Computer-mediated human inter-communication<\/p>\n<h2>Goals<\/h2>\n<ul>\n<li>Understand end-users&#8217; requirements<\/li>\n<li>Identify sensor(s) requirement<\/li>\n<li>Prototype new hardware<\/li>\n<li>Develop robust technologies<\/li>\n<\/ul>\n<h2>Publications<\/h2>\n<ul>\n<li><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/air-and-bone-conductive-integrated-microphones-for-robust-speech-detection-and-enhancement\/\">Air-and-Bone Conductive Integrated Microphones for Robust Speech Detection and Enhancement<\/a> in the IEEE Automatic Speech Recognition and Understanding Workshop (ASRU03), November 30 &#8211; December 4, 2003.<\/li>\n<li><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/multisensory-microphones-for-robust-speech-detection-enhancement-and-recognition\/\">Multi-Sensory Microphones for Robust Speech Detection, Enhancement and Recognition<\/a> in the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2004), May 17-21, 2004.<\/li>\n<li><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/direct-filtering-for-air-and-bone-conductive-microphones\/\">Direct Filtering for Air-and-Bone Conductive Microphones<\/a> in the IEEE International Workshop on Multimedia Signal Processing (MMSP&#8217;04), Sep.29-Oct.1, 2004.<\/li>\n<li><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/nonlinear-information-fusion-in-multi-sensor-processing-extracting-and-exploiting-hidden-dynamics-of-speech-captured-by-a-bone-conductive-microphone\/\">Nonlinear Information Fusion in Multi-Sensor Processing Extracting and Exploiting Hidden Dynamics of Speech Captured by a Bone-Conductive Microphone<\/a> in the IEEE International Workshop on Multimedia Signal Processing (MMSP&#8217;04), Sep.29-Oct.1, 2004.<\/li>\n<\/ul>\n<h2>Sample Waveforms (pending migration)<span style=\"text-decoration: underline;\"><strong><br \/>\n<\/strong><\/span><\/h2>\n<p><em>Original waveforms:<\/em><\/p>\n<ul>\n<li>Air channel<\/li>\n<li>Bone channel<\/li>\n<\/ul>\n<p><em>Processed waveforms:<\/em><\/p>\n<ul>\n<li>Spectral subtraction<\/li>\n<li>Direct filtering<\/li>\n<li>Minimum mean square error (MMSE) estimation with a single Gaussian<\/li>\n<li>Minimum mean square error (MMSE) estimation with a mixture of four Gaussians<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Project WITTY exploits multi-sensory information to improve user experience in\u00a0speech-centric human computer interaction and computer-mediated human inter-communication.<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"research-area":[13562],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-336623","msr-project","type-msr-project","status-publish","hentry","msr-research-area-computer-vision","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"2003-08-09","related-publications":[],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[],"msr_research_lab":[199565],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/336623"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":3,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/336623\/revisions"}],"predecessor-version":[{"id":642852,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/336623\/revisions\/642852"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=336623"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=336623"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=336623"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=336623"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=336623"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}