{"id":493,"date":"2016-05-06T17:44:06","date_gmt":"2016-05-06T21:44:06","guid":{"rendered":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/parsing-our-silent-language\/"},"modified":"2016-10-27T10:36:39","modified_gmt":"2016-10-27T14:36:39","slug":"parsing-our-silent-language","status":"publish","type":"post","link":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/parsing-our-silent-language\/","title":{"rendered":"Parsing our Silent Language"},"content":{"rendered":"<h2><em>Kat Sullivan<\/em><\/h2>\n<p>Parsing our Silent Language is a computer program that parses body language in real time utilizing machine learning and skeletal tracking.<\/p>\n<p><a href=\"https:\/\/itp.nyu.edu\/thesis2016\/project\/kat-sullivan\">https:\/\/itp.nyu.edu\/thesis2016\/project\/kat-sullivan<\/a><\/p>\n<div id='gallery-1' class='gallery galleryid-493 gallery-columns-0 gallery-size-medium'><figure class='gallery-item'>\n\t\t\t<div class='gallery-icon landscape'>\n\t\t\t\t<a href='https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-content\/uploads\/sites\/38\/2016\/05\/1462568788_image1.jpg'><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"169\" src=\"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-content\/uploads\/sites\/38\/2016\/05\/1462568788_image1-300x169.jpg\" class=\"attachment-medium size-medium\" alt=\"\" srcset=\"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-content\/uploads\/sites\/38\/2016\/05\/1462568788_image1-300x169.jpg 300w, https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-content\/uploads\/sites\/38\/2016\/05\/1462568788_image1-768x432.jpg 768w, https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-content\/uploads\/sites\/38\/2016\/05\/1462568788_image1-1024x576.jpg 1024w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/a>\n\t\t\t<\/div><\/figure>\n\t\t<\/div>\n\n<h3>Description<\/h3>\n<p>Parsing the Silent Language is software that analyzes nonverbal language using a Kinect and the C++ framework, Cinder. Coming from a movement background, I was curious why sentiment analysis placed all emphasis on our words when our body language can contradict or add depth to our words. I started this process by first manually, and then algorithmically, categorizing my own body language. However, I was inadvertently programming my own movement tendencies and as a result, the algorithms became biased to my own body. To address the issue, I enlisted the help of several graduate acting students and recorded their skeletal data while they acted out various emotions. I then used this data to train a classifier using machine learning, which now analyzes body language in real time.<\/p>\n<h3>Classes<\/h3>\n<p>Thesis<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Kat Sullivan Parsing our Silent Language is a computer program that parses body language in real time utilizing machine learning and skeletal tracking. https:\/\/itp.nyu.edu\/thesis2016\/project\/kat-sullivan Description Parsing the Silent Language is software that analyzes nonverbal language using a Kinect and the C++ framework, Cinder. Coming from a movement background, I was curious why sentiment analysis placed &hellip; <a href=\"https:\/\/itp.nyu.edu\/shows\/thesis2016\/parsing-our-silent-language\/\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">Parsing our Silent Language<\/span> <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":11,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1516,16126,462,28],"tags":[],"class_list":["post-493","post","type-post","status-publish","format-standard","hentry","category-andrew-lazarow","category-kat-sullivan","category-projects","category-thesis"],"_links":{"self":[{"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/posts\/493"}],"collection":[{"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/comments?post=493"}],"version-history":[{"count":2,"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/posts\/493\/revisions"}],"predecessor-version":[{"id":1993,"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/posts\/493\/revisions\/1993"}],"wp:attachment":[{"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/media?parent=493"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/categories?post=493"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/itp.nyu.edu\/shows\/thesis2016\/wp-json\/wp\/v2\/tags?post=493"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}