SSN_NLP at SemEval-2019 Task 3: Contextual Emotion Identification from Textual Conversation using Seq2Seq Deep Neural Network
Senthil Kumar B., Thenmozhi D., Aravindan Chandrabose, Srinethe Sharavanan
Abstract
Emotion identification is a process of identifying the emotions automatically from text, speech or images. Emotion identification from textual conversations is a challenging problem due to absence of gestures, vocal intonation and facial expressions. It enables conversational agents, chat bots and messengers to detect and report the emotions to the user instantly for a healthy conversation by avoiding emotional cues and miscommunications. We have adopted a Seq2Seq deep neural network to identify the emotions present in the text sequences. Several layers namely embedding layer, encoding-decoding layer, softmax layer and a loss layer are used to map the sequences from textual conversations to the emotions namely Angry, Happy, Sad and Others. We have evaluated our approach on the EmoContext@SemEval2019 dataset and we have obtained the micro-averaged F1 scores as 0.595 and 0.6568 for the pre-evaluation dataset and final evaluation test set respectively. Our approach improved the base line score by 7% for final evaluation test set.- Anthology ID:
- S19-2055
- Volume:
- Proceedings of the 13th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota, USA
- Editors:
- Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 318–323
- Language:
- URL:
- https://aclanthology.org/S19-2055
- DOI:
- 10.18653/v1/S19-2055
- Cite (ACL):
- Senthil Kumar B., Thenmozhi D., Aravindan Chandrabose, and Srinethe Sharavanan. 2019. SSN_NLP at SemEval-2019 Task 3: Contextual Emotion Identification from Textual Conversation using Seq2Seq Deep Neural Network. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 318–323, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
- Cite (Informal):
- SSN_NLP at SemEval-2019 Task 3: Contextual Emotion Identification from Textual Conversation using Seq2Seq Deep Neural Network (B. et al., SemEval 2019)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/S19-2055.pdf
- Data
- EmoContext