This invention relates to the field of
natural language processing technology, providing an end-to-end multi-turn dialogue
rewriting method,
system, and storage medium that integrates dialogue detection. In the proposed end-to-end multi-turn dialogue
rewriting method, a joint learning approach is used to
train the
detector and generator, solving the problems of cascading errors and incoherent sentences after matching and
filling in the Pipeline method, thus improving the
detector's
detection performance. By having the
detector ignore sentences that do not need
rewriting and integrating dialogue detection information into the generator, the
slow speed and repetitive encoding problems of the Seq2Seq method are solved. The dialogue rewriting process of this invention does not require the generator to repeatedly
encode the text, improving the model's prediction speed. Simultaneously, integrating dialogue detection information into the generator improves the generation quality of the rewritten sentences.