The invention relates to the field of
artificial intelligence, in particular to a man-
machine conversation understanding method and
system for a specific field and relevant equipment and aims to improve accuracy of conversation understanding. The conversation understanding method of the man-
machine conversation
system comprises the steps as follows: receiving a word currently input by a user and mapping the word to a vector space; expressing a historical word vector,
semantic annotation information and intent category information as vectors by using a
semantic representation layer; acquiring asemantic
label of the current word by using the
semantic labeling layer; acquiring the intent category of the current word by using an
intent recognition layer. Extra part-of-speech information is introduced during model training, the part-of-speech prediction layer is used for predicting the part-of-speech of the next input word,
semantic information shared by semantic annotations,
intent recognition and part-of-speech prediction is fully used and promoted mutually by joint
processing of the three tasks; the
system and the method have clear logic, high efficiency and high accuracy, and the technical problem that the existing man-
machine conversation system cannot effectively perform real-time conversation understanding is properly solved.