Automatic Summarization for Creative Writing: BART based Pipeline Method for Generating Summary of Movie Scripts
Aditya Upadhyay | Nidhir Bhavsar | Aakash Bhatnagar | Muskaan Singh | Petr Motlicek
Proceedings of The Workshop on Automatic Summarization for Creative Writing
This paper documents our approach for the Creative-Summ 2022 shared task for Automatic Summarization of Creative Writing. For this purpose, we develop an automatic summarization pipeline where we leverage a denoising autoencoder for pretraining sequence-to-sequence models and fine-tune it on a large-scale abstractive screenplay summarization dataset to summarize TV transcripts from primetime shows. Our pipeline divides the input transcript into smaller conversational blocks, removes redundant text, summarises the conversational blocks, obtains the block-wise summaries, cleans, structures, and then integrates the summaries to create the meeting minutes. Our proposed system achieves some of the best scores across multiple metrics(lexical, semantical) in the Creative-Summ shared task.