{"65166":{"#nid":"65166","#data":{"type":"news","title":"Chordia Receives NSF CAREER Award for Research in Predictive Models of Music","body":[{"value":"\u003Cp\u003EGeorgia Tech assistant professor \u003Ca href=\u0022http:\/\/www.music.gatech.edu\/people\/parag-p-chordia\u0022 target=\u0022_self\u0022\u003EParag Chordia\u003C\/a\u003E has been awarded the prestigious Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF) to advance his research in predictive models of music. Chordia heads the Music Intelligence Group in the \u003Ca href=\u0022http:\/\/gtcmt.gatech.edu\u0022 target=\u0022_blank\u0022\u003EGeorgia Tech Center for Music Technology\u003C\/a\u003E.\u003C\/p\u003E\u003Cp\u003E\u201cWhen a person is listening to a song, she is anticipating, at any given moment, the timing and nature of the next event by decoding the musical signal,\u201d Chordia explained. \u201cEven when analyzing a simple song, the brain utilizes complex correlations between the musical elements to make accurate predictions. Musical signals are richly patterned, with long-term dependencies, dependencies across time-scales and correlations between parallel information streams; the melody depends on the rhythm, the rhythmic patterns depend on the form and the intonation of the pitch depends on the placement within the phrase.\u201d\n\u003C\/p\u003E\u003Cp\u003EThe goal of this project is to develop machine-learning (ML) models for predicting temporally structured events in the context of music, which take advantage of these complex correlations, and to use these models to help explain human musical expectation. \u003C\/p\u003E\u003Cp\u003E \nThe project builds on Chordia\u0027s previous research, which focused on understanding musical creativity from cognitive and computational perspectives and was funded by a creativeIT grant from the NSF.  More generally, the project is an outgrowth of his research in creating algorithms that can interpret and generate music to enhance and enable human creativity. An example is LaDiDa, a top-ten music iPhone app, that automatically composes music in response to solo singing and was commercialized from research in Chordia\u0027s lab.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EChordia aims to develop machine-learning models for predicting temporally structured events in the context of music.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":"","uid":"27213","created_gmt":"2011-03-27 18:58:42","changed_gmt":"2016-10-08 03:08:26","author":"Teri Nagel","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2011-03-27T00:00:00-04:00","iso_date":"2011-03-27T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"54859":{"id":"54859","type":"image","title":"Parag Chordia - profile","body":null,"created":"1449175474","gmt_created":"2015-12-03 20:44:34","changed":"1475894483","gmt_changed":"2016-10-08 02:41:23","alt":"Parag Chordia - profile","file":{"fid":"179927","name":"Parag_Chordia.jpg","image_path":"\/sites\/default\/files\/images\/Parag_Chordia_1.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/Parag_Chordia_1.jpg","mime":"image\/jpeg","size":13888,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/Parag_Chordia_1.jpg?itok=KGuUnxPO"}}},"media_ids":["54859"],"groups":[{"id":"1221","name":"College of Design"}],"categories":[{"id":"134","name":"Student and Faculty"}],"keywords":[{"id":"1936","name":"Center for Music Technology"},{"id":"1180","name":"Music"},{"id":"1309","name":"music technology"},{"id":"363","name":"NSF"},{"id":"1929","name":"Parag Chordia"},{"id":"167096","name":"school of music"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:teri.nagel@coa.gatech.edu\u0022 target=\u0022_blank\u0022\u003ETeri Nagel\u003C\/a\u003E, Georgia Tech College of Architecture, 404-385-2156\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}