Design and Research of Intelligent QA System for Flight Crew Operating Manual

Aviation flight crews rely on a large number of complex standard documents and operation manuals when performing flight tasks. In order to relieve the pressure of manual retrieval of documents, intelligent question-answering technology based on reading comprehension is gradually applied. In this paper, the flight crew operation manual SQuAD dataset is studied and built, based on which the reader-retriever framework of text content-based reading question answering system (TCQA) is analyzed and established. Experiments are conducted to compare the relevant indexes of the QA system with different combinations of reader and retriever models under the open-source tool haystack. Based on the comparison of response speed and retrieval capability, the best model combination is obtained for the flight crew operation manual dataset, and suggestions are made for the model-related performance improvement.