Abstract
This work examines the rhetorical techniques that speakers employ during political campaigns. We introduce a new corpus of speeches from campaign events in the months leading up to the 2016 U.S. presidential election and develop new models for predicting moments of audience applause. In contrast to existing datasets, we tackle the challenge of working with transcripts that derive from uncorrected closed captioning, using associated audio recordings to automatically extract and align labels for instances of audience applause. In prediction experiments, we find that lexical features carry the most information, but that a variety of features are predictive, including prosody, long-term contextual dependencies, and theoretically motivated features designed to capture rhetorical techniques.- Anthology ID:
- N18-1009
- Volume:
- Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 92–102
- Language:
- URL:
- https://aclanthology.org/N18-1009
- DOI:
- 10.18653/v1/N18-1009
- Cite (ACL):
- Jon Gillick and David Bamman. 2018. Please Clap: Modeling Applause in Campaign Speeches. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 92–102, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Please Clap: Modeling Applause in Campaign Speeches (Gillick & Bamman, NAACL 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/N18-1009.pdf