Scene Boundary Detection from Movie Dialogue: A Genetic Algorithm Approach

Movie scripts are a rich textual resource that can be tapped for movie content analysis. This article describes a mechanism for fragmenting a sequence of movie script dialogue into scene-wise groups. In other words, it attempts to locate scene transitions using information acquired from a sequence of dialogue units. We collect movie scripts from a web archive. Thereafter, we preprocess them to develop a resource of dialogues. We feed the dialogue sequence from a script to a Genetic Algorithm (GA) framework. The system fragments the sequence into adjacent groups of dialogue units or output 'scenes'. We use SentiWordnet scores and Wordnet distance for dialogue units to optimize this grouping so that adjacent scenes are semantically most dissimilar. Then we compare the resulting fragmented dialogue sequence with the original scene-wise alignment of dialogue in the script.

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