Abstract
We construct the first ever multimodal sarcasm dataset for Spanish. The audiovisual dataset consists of sarcasm annotated text that is aligned with video and audio. The dataset represents two varieties of Spanish, a Latin American variety and a Peninsular Spanish variety, which ensures a wider dialectal coverage for this global language. We present several models for sarcasm detection that will serve as baselines in the future research. Our results show that results with text only (89%) are worse than when combining text with audio (91.9%). Finally, the best results are obtained when combining all the modalities: text, audio and video (93.1%). Our dataset will be published on Zenodo with access granted by request.- Anthology ID:
- 2021.maiworkshop-1.9
- Volume:
- Proceedings of the Third Workshop on Multimodal Artificial Intelligence
- Month:
- June
- Year:
- 2021
- Address:
- Mexico City, Mexico
- Editors:
- Amir Zadeh, Louis-Philippe Morency, Paul Pu Liang, Candace Ross, Ruslan Salakhutdinov, Soujanya Poria, Erik Cambria, Kelly Shi
- Venue:
- maiworkshop
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 63–68
- Language:
- URL:
- https://aclanthology.org/2021.maiworkshop-1.9
- DOI:
- 10.18653/v1/2021.maiworkshop-1.9
- Cite (ACL):
- Khalid Alnajjar and Mika Hämäläinen. 2021. ¡Qué maravilla! Multimodal Sarcasm Detection in Spanish: a Dataset and a Baseline. In Proceedings of the Third Workshop on Multimodal Artificial Intelligence, pages 63–68, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- ¡Qué maravilla! Multimodal Sarcasm Detection in Spanish: a Dataset and a Baseline (Alnajjar & Hämäläinen, maiworkshop 2021)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2021.maiworkshop-1.9.pdf