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			<subfield code="a">CONF</subfield>
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			<subfield code="a">Chittaranjan_FG11_2011/IDIAP</subfield>
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		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">Exploiting observers' judgements for nonverbal group interaction analysis</subfield>
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		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Chittaranjan, Gokul</subfield>
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		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Aran, Oya</subfield>
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		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Gatica-Perez, Daniel</subfield>
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		<datafield tag="856" ind1="4" ind2="0">
			<subfield code="i">EXTERNAL</subfield>
			<subfield code="u">http://publications.idiap.ch/attachments/papers/2011/Chittaranjan_FG11_2011.pdf</subfield>
			<subfield code="x">PUBLIC</subfield>
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		<datafield tag="711" ind1="2" ind2=" ">
			<subfield code="a">IEEE Conference on Automatic Face and Gesture Recognition</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2011</subfield>
			<subfield code="b">IEEE</subfield>
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		<datafield tag="773" ind1=" " ind2=" ">
			<subfield code="c">6</subfield>
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		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">Incorporating annotators' knowledge into a machine-learning framework for detecting psychological traits using multimodal data is an open issue in human communication and social computing. We present a model that is designed to exploit the subjective judgements of multiple annotators on a social trait labeling task. Our two-stage model first estimates a ground truth by modeling the annotators using both the annotations and annotators’ self-reported confidences. In the second stage, we train a classifier using the estimated ground truth as labels. We also define ways to verify the consistency of our model and validate it using annotations and nonverbal cues for a dominance estimation task in a group interaction scenario on the publicly available DOME corpus, in addition to synthetically generated data. Our models give satisfactory results, outperforming the commonly used majority voting as well as other approaches in the literature.</subfield>
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