🔥 🔥 🔥 Notice: This repository will no longer be maintained. Instead, we are are moving all our multimodal works to this new centralized repository: https://github.com/declare-lab/multimodal-deep-learning.

Contextual Inter-modal Attention for Multi-modal Sentiment Analysis

Code for the paper Contextual Inter-modal Attention for Multi-modal Sentiment Analysis (EMNLP 2018).

Dataset

We provide results on the MOSI dataset.
Please cite the creators.

Requirements:

Python 3.5
Keras (Tensorflow backend) 2.2.4
Scikit-learn 0.20.0

Experiments

python create_data.py
python trimodal_attention_models.py

Citation

If you use this code in your research, please cite our work using:

@inproceedings{ghosal2018contextual,
  title={Contextual Inter-modal Attention for Multi-modal Sentiment Analysis},
  author={Ghosal, Deepanway and Akhtar, Md Shad and Chauhan, Dushyant and Poria, Soujanya and Ekbal, Asif and Bhattacharyya, Pushpak},
  booktitle={Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing},
  pages={3454--3466},
  year={2018}
}

Credits

Some of the functionalities in this repo are borrowed from https://github.com/soujanyaporia/contextual-utterance-level-multimodal-sentiment-analysis

Authors

Deepanway Ghosal