Prediction of Audience Response from Spoken Sequences, Speech Pauses and Co-speech Gestures in Humorous Discourse by Barack Obama
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Prediction of Audience Response from Spoken Sequences, Speech Pauses and Co-speech Gestures in Humorous Discourse by Barack Obama. / Navarretta, Costanza.
8th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2017 Proceedings. IEEE, 2017. p. 327-331.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Prediction of Audience Response from Spoken Sequences, Speech Pauses and Co-speech Gestures in Humorous Discourse by Barack Obama
AU - Navarretta, Costanza
N1 - Conference code: 8
PY - 2017
Y1 - 2017
N2 - In this paper, we aim to predict audience responsefrom simple spoken sequences, speech pauses and co-speechgestures in annotated video- and audio-recorded speeches byBarack Obama at the Annual White House Correspondents’Association Dinner in 2011 and 2016. At these dinners, theAmerican president mocks himself, his collaborators, politicaladversary and the press corps making the audience react withcheers, laughter and/or applause. The results of the prediction experimentdemonstrate that information about spoken sequences,pauses and co-speech gestures by Obama can be used to predictthe immediate audience response. This confirms and shows anapplication of numerous studies that address the importance ofspeech pauses and gestures in delivering the discourse messagein a successful way. The fact that machine learning algorithmscan use information about pauses and gestures to build modelsof audience reaction is also relevant for the construction ofintelligent and cognitively based multimodal ICT.
AB - In this paper, we aim to predict audience responsefrom simple spoken sequences, speech pauses and co-speechgestures in annotated video- and audio-recorded speeches byBarack Obama at the Annual White House Correspondents’Association Dinner in 2011 and 2016. At these dinners, theAmerican president mocks himself, his collaborators, politicaladversary and the press corps making the audience react withcheers, laughter and/or applause. The results of the prediction experimentdemonstrate that information about spoken sequences,pauses and co-speech gestures by Obama can be used to predictthe immediate audience response. This confirms and shows anapplication of numerous studies that address the importance ofspeech pauses and gestures in delivering the discourse messagein a successful way. The fact that machine learning algorithmscan use information about pauses and gestures to build modelsof audience reaction is also relevant for the construction ofintelligent and cognitively based multimodal ICT.
M3 - Article in proceedings
SN - ISBN 978-1-5386-1264-4
SP - 327
EP - 331
BT - 8th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2017 Proceedings
PB - IEEE
T2 - International Conference on Cognitive Infocommunications
Y2 - 11 September 2017 through 14 September 2017
ER -
ID: 183607810