In this research we aim to detect subjective sentences in spontaneous speech and label them for polarity. We introduce a novel technique wherein subjective patterns are learned from both labeled and unlabeled data, using n-grams with varying levels of lexical instantiation. Applying this technique to meeting speech, we gain significant improvement over state-of-the-art approaches and demonstrate the methodÂ’s robustness to ASR errors. We also show that coupling the pattern-based approach with structural and lexical features of meetings yields additional improvement.
Cite as: Murray, G., Carenini, G. (2009) Detecting subjectivity in multiparty speech. Proc. Interspeech 2009, 2007-2010, doi: 10.21437/Interspeech.2009-578
@inproceedings{murray09_interspeech,
author={Gabriel Murray and Giuseppe Carenini},
title={{Detecting subjectivity in multiparty speech}},
year=2009,
booktitle={Proc. Interspeech 2009},
pages={2007--2010},
doi={10.21437/Interspeech.2009-578}
}