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Multimodal (text, acoustic, visual) Sentiment Analysis and Emotion Recognition on CMU-MOSEI dataset.

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Multimodal CNN

Convolutional Neural Network for Multimodal Sentiment Analysis and Emotion Recognition on CMU-MOSEI dataset.

Clone the repo. Download the data (h5 files) from here and unzip it. The folder data_h5 should contain egemaps_c.h5, openface_c.h5, bert_c.h5. Ready to go.

Specify hyperparameters in parameters.py and run ./train_model_multimodal.py

Files

parameters.py --> parameters of the dataset, model, and task ('sentiment', 'sentiment_binary', or 'emotion').

dataset_multimodal.py --> DataLoader class to load h5 files

models.py --> CNN architectures for sentiment regression prediction, binary classification, and emotion recognition.

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Multimodal (text, acoustic, visual) Sentiment Analysis and Emotion Recognition on CMU-MOSEI dataset.

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