@inproceedings{chakravartula-indurthi-2019-emominer,
title = "{EMOMINER} at {S}em{E}val-2019 Task 3: A Stacked {B}i{LSTM} Architecture for Contextual Emotion Detection in Text",
author = "Chakravartula, Nikhil and
Indurthi, Vijayasaradhi",
editor = "May, Jonathan and
Shutova, Ekaterina and
Herbelot, Aurelie and
Zhu, Xiaodan and
Apidianaki, Marianna and
Mohammad, Saif M.",
booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S19-2033",
doi = "10.18653/v1/S19-2033",
pages = "205--209",
abstract = "This paper describes our participation in the SemEval 2019 Task 3 - Contextual Emotion Detection in Text. This task aims to identify emotions, viz. happiness, anger, sadness in the context of a text conversation. Our system is a stacked Bidirectional LSTM, equipped with attention on top of word embeddings pre-trained on a large collection of Twitter data. In this paper, apart from describing our official submission, we elucidate how different deep learning models respond to this task.",
}
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%0 Conference Proceedings
%T EMOMINER at SemEval-2019 Task 3: A Stacked BiLSTM Architecture for Contextual Emotion Detection in Text
%A Chakravartula, Nikhil
%A Indurthi, Vijayasaradhi
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F chakravartula-indurthi-2019-emominer
%X This paper describes our participation in the SemEval 2019 Task 3 - Contextual Emotion Detection in Text. This task aims to identify emotions, viz. happiness, anger, sadness in the context of a text conversation. Our system is a stacked Bidirectional LSTM, equipped with attention on top of word embeddings pre-trained on a large collection of Twitter data. In this paper, apart from describing our official submission, we elucidate how different deep learning models respond to this task.
%R 10.18653/v1/S19-2033
%U https://aclanthology.org/S19-2033
%U https://doi.org/10.18653/v1/S19-2033
%P 205-209
Markdown (Informal)
[EMOMINER at SemEval-2019 Task 3: A Stacked BiLSTM Architecture for Contextual Emotion Detection in Text](https://aclanthology.org/S19-2033) (Chakravartula & Indurthi, SemEval 2019)
ACL