01620nas a2200349 4500008004100000020002200041245006600063210006600129260003200195520052200227653001900749653001900768653002800787653003500815653001300850653003900863653001400902653002300916653002400939653001700963653001100980653003900991653002101030653000901051653002501060653001501085653001501100653003001115100001501145700001701160856009301177 2008 eng d a978-1-4244-2661-400aAutomatic cry detection in early childhood education settings0 aAutomatic cry detection in early childhood education settings aMonterey, CAbIEEEc08/20083 a
We present results on applying a novel machine learning approach for learning auditory moods in natural environments [1] to the problem of detecting crying episodes in preschool classrooms. The resulting system achieved levels of performance approaching that of human coders and also significantly outperformed previous approaches to this problem [2].
10aAcoustic noise10aauditory moods10aautomatic cry detection10abehavioural sciences computing10aDeafness10aearly childhood education settings10aeducation10aEducational robots10aEmotion recognition10ahuman coders10aHumans10alearning (artificial intelligence)10aMachine Learning10aMood10apreschool classrooms10aPrototypes10aRobustness10aWorking environment noise1 aRuvolo, P.1 aMovellan, J. uhttps://rubi.ucsd.edu/content/automatic-cry-detection-early-childhood-education-settings