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EMNLP
2009

Predicting Subjectivity in Multimodal Conversations

10 years 2 months ago
Predicting Subjectivity in Multimodal Conversations
In this research we aim to detect subjective sentences in multimodal conversations. We introduce a novel technique wherein subjective patterns are learned from both labeled and unlabeled data, using n-gram word sequences with varying levels of lexical instantiation. Applying this technique to meeting speech and email conversations, we gain significant improvement over state-of-the-art approaches. Furthermore, we show that coupling the pattern-based approach with features that capture characteristics of general conversation structure yields additional improvement.
Gabriel Murray, Giuseppe Carenini
Added 17 Feb 2011
Updated 17 Feb 2011
Type Journal
Year 2009
Where EMNLP
Authors Gabriel Murray, Giuseppe Carenini
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