Adversarial Attention Modeling for Multi-dimensional Emotion Regres...

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AAN
Adversarial Attention Modeling for
Multi-dimensional Emotion Regression
ACL, 2019
Suyang Zhu, Shoushan Li, Guodong Zho...

AAN
Table of contents
1 Abstract
2 Introduction
3 Adversarial Attention Network
4 Experimentation
5 Conclusion
2 / 34

AAN
Abstract
Table of contents
1 Abstract
2 Introduction
3 Adversarial Attention Network
4 Experimentation
5 Conclusion
3 ...

AAN
Abstract
Abstract
To improve Reader′s and Writer′s for multi-dimensional emotion
regression tasks with EMOBANK, this p...

AAN
Introduction
Table of contents
1 Abstract
2 Introduction
3 Adversarial Attention Network
4 Experimentation
5 Conclusio...

AAN
Introduction
Introduction
Analyzing emotion can be divided into:
Emotion classification [1]
Emotion regression [8]
Due...

AAN
Introduction
Introduction (Cont.)
Nowadays, there are many emotion regression corpora [4].
These emotion regression co...

AAN
Introduction
Introduction (Cont.)
For this paper, they solve multi-dimensional emotion regression via a
joint approach...

AAN
Introduction
Contribution
They propose an Adversarial Attention Network (AAN). It conducts
adversarial learning betwee...

AAN
Adversarial Attention Network
Table of contents I
1 Abstract
2 Introduction
3 Adversarial Attention Network
Attention ...

AAN
Adversarial Attention Network
Table of contents II
5 Conclusion
11 / 34

AAN
Adversarial Attention Network
Figure 1: The framework of the Valence-Arousal Adversarial Attention
Network which condu...

AAN
Adversarial Attention Network
Attention Modeling
Attention Modeling
AAN takes a sequence of word vectors X = [x1 x2 . ...

AAN
Adversarial Attention Network
Attention Modeling
Attention Modeling (Cont.)
AAN has three attention layers, denoted as...

AAN
Adversarial Attention Network
Feature Extraction
Feature Extraction
The feature extractor is trained to extract the fe...

AAN
Adversarial Attention Network
Feature Extraction
Feature Extraction (Cont.)
The output feature vector Feat set as:
Fea...

AAN
Adversarial Attention Network
Dimensional Emotion Regression
Dimensional Emotion Regression
They implement the regress...

AAN
Adversarial Attention Network
Dimensional Emotion Regression
Dimensional Emotion Regression (Cont.)
AAN’s regressor se...

AAN
Adversarial Attention Network
Emotion Dimension Discrimination
Emotion Dimension Discrimination
The discriminator D ju...

AAN
Adversarial Attention Network
Emotion Dimension Discrimination
Emotion Dimension Discrimination (Cont.)
The discrimina...

AAN
Adversarial Attention Network
Adversarial Training
Adversarial Training
Firstly, they train AttV, AttA, AttS, RV, RA a...

AAN
Adversarial Attention Network
Adversarial Training
Adversarial Training (Cont.)
Then, they update the parameters of D ...

AAN
Adversarial Attention Network
Adversarial Training
Adversarial Training (Cont.)
Finally, they update the parameters of...

AAN
Experimentation
Table of contents
1 Abstract
2 Introduction
3 Adversarial Attention Network
4 Experimentation
5 Conclu...

AAN
Experimentation
Experiment Settings
Compared with other baselines, they apply AAN to the EMOBANK
Reader′s and Writer′s...

AAN
Experimentation
Experiment Settings (Cont.)
Table 2: List of hyper parameters during AAN training.
They apply the wide...

AAN
Experimentation
Baselines
Deep CNN [3]
Regional CNN-LSTM [8]
Context LSTM-CNN [7]
Attention Network
Joint Learning
27 ...

AAN
Experimentation
Table 3: The r-values of all the evaluated approaches.
28 / 34

AAN
Conclusion
Table of contents
1 Abstract
2 Introduction
3 Adversarial Attention Network
4 Experimentation
5 Conclusion
...

AAN
Conclusion
Conclusion
In this paper, they propose an Adversarial Attention Network (AAN)
for multi-dimensional emotion...

AAN
Conclusion
References I
[1] Muhammad Abdul-Mageed and Lyle Ungar. “EmoNet:
Fine-Grained Emotion Detection with Gated R...

AAN
Conclusion
References II
[4] Sven Buechel and Udo Hahn. “EmoBank: Studying the Impact
of Annotation Perspective and Re...

AAN
Conclusion
References III
[6] Ryo Masumura, Yusuke Shinohara, et al. “Adversarial Training
for Multi-task and Multi-li...

AAN
Conclusion
References IV
[8] Jin Wang, Liang-Chih Yu, et al. “Dimensional Sentiment
Analysis Using a Regional CNN-LSTM...

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