@inproceedings{wang-etal-2016-bilingual,
title = "A Bilingual Attention Network for Code-switched Emotion Prediction",
author = "Wang, Zhongqing and
Zhang, Yue and
Lee, Sophia and
Li, Shoushan and
Zhou, Guodong",
editor = "Matsumoto, Yuji and
Prasad, Rashmi",
booktitle = "Proceedings of {COLING} 2016, the 26th International Conference on Computational Linguistics: Technical Papers",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/C16-1153",
pages = "1624--1634",
abstract = "Emotions in code-switching text can be expressed in either monolingual or bilingual forms. However, relatively little research has emphasized on code-switching text. In this paper, we propose a Bilingual Attention Network (BAN) model to aggregate the monolingual and bilingual informative words to form vectors from the document representation, and integrate the attention vectors to predict the emotion. The experiments show that the effectiveness of the proposed model. Visualization of the attention layers illustrates that the model selects qualitatively informative words.",
}
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<abstract>Emotions in code-switching text can be expressed in either monolingual or bilingual forms. However, relatively little research has emphasized on code-switching text. In this paper, we propose a Bilingual Attention Network (BAN) model to aggregate the monolingual and bilingual informative words to form vectors from the document representation, and integrate the attention vectors to predict the emotion. The experiments show that the effectiveness of the proposed model. Visualization of the attention layers illustrates that the model selects qualitatively informative words.</abstract>
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%0 Conference Proceedings
%T A Bilingual Attention Network for Code-switched Emotion Prediction
%A Wang, Zhongqing
%A Zhang, Yue
%A Lee, Sophia
%A Li, Shoushan
%A Zhou, Guodong
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F wang-etal-2016-bilingual
%X Emotions in code-switching text can be expressed in either monolingual or bilingual forms. However, relatively little research has emphasized on code-switching text. In this paper, we propose a Bilingual Attention Network (BAN) model to aggregate the monolingual and bilingual informative words to form vectors from the document representation, and integrate the attention vectors to predict the emotion. The experiments show that the effectiveness of the proposed model. Visualization of the attention layers illustrates that the model selects qualitatively informative words.
%U https://aclanthology.org/C16-1153
%P 1624-1634
Markdown (Informal)
[A Bilingual Attention Network for Code-switched Emotion Prediction](https://aclanthology.org/C16-1153) (Wang et al., COLING 2016)
ACL