"Yeah Right": Sarcasm Recognition for Spoken Dialogue Systems (bibtex)
by Tepperman, Joseph, Traum, David and Narayanan, Shrikanth
Abstract:
The robust understanding of sarcasm in a spoken dialogue system requires a reformulation of the dialogue manager's basic assumptions behind, for example, user behavior and grounding strategies. But automatically detecting a sarcastic tone of voice is not a simple matter. This paper presents some experiments toward sarcasm recognition using prosodic, spectral, and contextual cues. Our results demonstrate that spectral and contextual features can be used to detect sarcasm as well as a human annotator would, and confirm a long-held claim in the field of psychology — that prosody alone is not sufficient to discern whether a speaker is being sarcastic.
Reference:
"Yeah Right": Sarcasm Recognition for Spoken Dialogue Systems (Tepperman, Joseph, Traum, David and Narayanan, Shrikanth), In Interspeech 2006, 2006.
Bibtex Entry:
@inproceedings{tepperman_yeah_2006,
	address = {Pittsburgh, PA},
	title = {"{Yeah} {Right}": {Sarcasm} {Recognition} for {Spoken} {Dialogue} {Systems}},
	url = {http://ict.usc.edu/pubs/Yeah%20Right-%20Sarcasm%20Recognition%20for%20Spoken%20Dialogue%20Systems.pdf},
	abstract = {The robust understanding of sarcasm in a spoken dialogue system requires a reformulation of the dialogue manager's basic assumptions behind, for example, user behavior and grounding strategies. But automatically detecting a sarcastic tone of voice is not a simple matter. This paper presents some experiments toward sarcasm recognition using prosodic, spectral, and contextual cues. Our results demonstrate that spectral and contextual features can be used to detect sarcasm as well as a human annotator would, and confirm a long-held claim in the field of psychology — that prosody alone is not sufficient to discern whether a speaker is being sarcastic.},
	booktitle = {Interspeech 2006},
	author = {Tepperman, Joseph and Traum, David and Narayanan, Shrikanth},
	month = sep,
	year = {2006},
	keywords = {Virtual Humans}
}
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