Scenarized semantic comprehension and dialogue generation method and system

Abstract

The invention provides a scenarized semantic comprehension and dialogue generation method and a scenarized semantic comprehension and dialogue generation system. The method comprises the steps of: establishing a user scene model, selecting and determining the field of a current conversation according to a result of a word segmentation system; understanding an interactive content of the round based on a corresponding scenarized user model by use of a selected scene semantic parser; and calling a dialogue generator in a corresponding scene, carrying out a dialogue synthesis and generating a dialogue result after interaction of the round in combination with an intermediate state of dialogue management. According to the scenarized semantic comprehension and dialogue generation method and the scenarized semantic comprehension and dialogue generation system, natural language understanding for a sentence and a phrase is simply and efficiently realized, and the situation that a computer automatically and completely understands a short text is realized. Automatic deep understanding and dialogue interaction of the computer for the sentence or the phrase of a natural language are realized and the purpose that a user needs a machine to understand the interaction language use automatically and accurately is achieved.

Description

Technical field [0001] The present invention relates to a scene-based semantic understanding and dialogue generation method, which belongs to the fields of natural language analysis, processing and semantic understanding, in particular to a natural language semantic understanding method under specific scenarios. Background technique [0002] The development of artificial intelligence technology has a long history, and natural language understanding technology, which is one of the most important directions in the field of artificial intelligence, has always been a research hotspot. It can be said that it has been a dream of mankind to let computers understand natural language. At present, natural language understanding technologies mainly use two major types of theoretical technologies, rule-based and statistics-based. The construction of a rule-based natural language understanding system is relatively complex, and it mainly faces the understanding of restricted domains. The stat...

AI Technical Summary

Problems solved by technology

[0012] The purpose of the present invention is to provide a scene-based semantic understanding and dialogue generation method, which can flexibly adapt to short text semantic understanding and dialogue in different scenes, solve the complex system existing in the prior art, heavily rely on linguistic expert knowledge, and Issues such as the limitation of audio data in short texts

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