Paper: Multimodal Subjectivity Analysis of Multiparty Conversation

ACL ID D08-1049
Title Multimodal Subjectivity Analysis of Multiparty Conversation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008
Authors

We investigate the combination of several sources of information for the purpose of sub- jectivity recognition and polarity classification in meetings. We focus on features from two modalities, transcribed words and acoustics, and we compare the performance of three dif- ferent textual representations: words, charac- ters, and phonemes. Our experiments show that character-level features outperform word- level features for these tasks, and that a care- ful fusion of all features yields the best perfor- mance. 1