Unsupervised Script Summarization Based on Pre-trained Model

Abstract

The script is a special text structure,which is composed of the dialogue between characters and the description of the scene.Unsupervised script summary refers to compressing and extracting a long script to form a short text that can summarize the information of the script.Therefore,this paper proposes an unsupervised script summary method based on a pre-training mo-del.By adding pre-training tasks for text sequence processing in pre-training,the generated pre-training model fully takes into account the description of the dialogue in the script and the emotional characteristics of the characters,then the model is used as a trainer to calculate the similarity between sentences and combined with the TextRank algorithm to score and sort the key sentences.Finally,the sentence with the highest score is selected as the summary.Experimental results show that the proposed method has better performance than the base model,and the performance is significantly improved in the ROUGE evaluation.

Keywords

• pre-trained model|pre-training task|script summary|unsupervised|sentence similarity|dialogue