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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.
Ruvolo et al. (Fri,) studied this question.
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