Abstract
In this paper, we present our system submission for the EmoContext, the third task of the SemEval 2019 workshop. Our solution is a hierarchical recurrent neural network with ELMo embeddings and regularization through dropout and Gaussian noise. We have mainly experimented with two main model architectures: simple and hierarchical LSTM network. We have also examined ensembling of the models and various variants of an ensemble. We have achieved microF1 score of 0.7481, which is significantly higher than baseline and currently the 19th best submission.- Anthology ID:
- S19-2046
- Volume:
- Proceedings of the 13th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota, USA
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 272–276
- Language:
- URL:
- https://aclanthology.org/S19-2046
- DOI:
- 10.18653/v1/S19-2046
- Cite (ACL):
- Michal Farkas and Peter Lacko. 2019. NL-FIIT at SemEval-2019 Task 3: Emotion Detection From Conversational Triplets Using Hierarchical Encoders. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 272–276, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
- Cite (Informal):
- NL-FIIT at SemEval-2019 Task 3: Emotion Detection From Conversational Triplets Using Hierarchical Encoders (Farkas & Lacko, SemEval 2019)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S19-2046.pdf
- Data
- EmoContext