Author : Furrer Stanislas
Date : 01.06.2020
In this paper, we present a data-driven approach to the segmentation of subtitles in movie into a speaker-aligned dataset. On this novel dataset, we applied our pre-train BERT model to label the dialogues with emotions. A Social bot was finally trained with our novel dataset in order to catch emotions in text conversations.
My Paper : Emotion Analysis on OpenSubtitles
ArXiv Paper : Fine-grained Emotion and Intent Learning in Movie Dialogues
The project is organized as follow :
- Preprocessing
- Load Opensubtitle
- Applied a Basic segmentation to produce a dialogues based dataset
- Implement two distincts data-driven segmentation
- Data Analysis
Compute basics statistics on:
- The Original Opensubtitle
- The two Automatic segmented subset
- Emo_bert_Training.ipynb :
Testing our Emo-Bert classifier on our new datasets.
- Results_analysis.ipynb :
Plot our different analysis and analyse the classification performance with other states-of-the-Art algorithm of Emotion Classification
Related Paper: ”Automatic turn segmentation for Movie & TV subtitles”, P. Lison and R. Meena, (2016)