<?xml version="1.0" encoding="UTF-8"?>
<collection xmlns="http://www.loc.gov/MARC21/slim">
	<record>
		<datafield tag="980" ind1=" " ind2=" ">
			<subfield code="a">CONF</subfield>
		</datafield>
		<datafield tag="970" ind1=" " ind2=" ">
			<subfield code="a">Chittaranjan_ICASSP2010_2010/IDIAP</subfield>
		</datafield>
		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">Are you a Werewolf? Detecting deceptive roles and outcomes in a conversational role-playing game</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Chittaranjan, Gokul</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Hung, Hayley</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">deception</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">Nonverbal behavior</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">role analysis</subfield>
		</datafield>
		<datafield tag="856" ind1="4" ind2="0">
			<subfield code="i">EXTERNAL</subfield>
			<subfield code="u">http://publications.idiap.ch/attachments/papers/2010/Chittaranjan_ICASSP2010_2010.pdf</subfield>
			<subfield code="x">PUBLIC</subfield>
		</datafield>
		<datafield tag="711" ind1="2" ind2=" ">
			<subfield code="a">IEEE International Conference on Acoustics, Speech and Signal Processing</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2010</subfield>
		</datafield>
		<datafield tag="771" ind1="2" ind2=" ">
			<subfield code="d">March 2010</subfield>
		</datafield>
		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">This paper addresses the task of automatically detecting outcomes of social interaction patterns, using non-verbal audio cues in competi- tive role-playing games (RPGs). For our experiments, we introduce a new data set which features 3 hours of audio-visual recordings of the popular â€œAre you a Werewolf?â€ RPG. Two problems are ap- proached in this paper: Detecting lying or suspicious behavior using non-verbal audio cues in a social context and predicting participantsâ€™ decisions in a game-day by analyzing speaker turns. Our best clas- sifier exhibits a performance improvement of 87% over the baseline for detecting deceptive roles. Also, we show that speaker turn based features can be used to determine the outcomes in the initial stages of the game, when the group is large.</subfield>
		</datafield>
	</record>
</collection>