The system takes an image as input and generates a coherent short story by combining image-sentence embeddings with a conditional neural language model. It leverages skip-thought vectors for semantic text understanding and applies a style-shifting operation inspired by neural style transfer to convert standard image captions into the style of novel narratives. The model was trained on Microsoft COCO captions without additional story-image paired data.