Multi-round spoken language understanding method, system and device based on dialogue logic

Abstract

The invention belongs to the technical field of man-machine conversation, particularly relates to a multi-round spoken language understanding method, system and device based on conversation logic, andaims to solve the problem that an existing multi-round spoken language understanding method is low in historical conversation data utilization rate. The method of the system comprises the steps of obtaining current dialogue data and historical dialogue data; respectively encoding the current dialogue data and the historical dialogue data into an input vector and a memory vector through a bidirectional gated recurrent neural network; generating a context knowledge vector through a memory retrieval method based on an attention mechanism according to the input vector and the memory vector; and obtaining intention classification information and semantic slot filling information of the current dialogue data through a multi-round spoken language understanding model based on the context knowledge vector and the current dialogue data. Historical dialogue data can be efficiently utilized in multiple rounds of spoken language understanding, and the performance of language understanding in multiple rounds of scenes is improved.

Description

technical field [0001] The invention belongs to the technical field of man-machine dialogue, and in particular relates to a dialogue logic-based multi-round spoken language comprehension method, system and device. Background technique [0002] A task-based dialogue system is a human-computer interaction system that assists users to complete tasks in a specific field (such as restaurants, hotels, or airline tickets) through natural language interaction. A task-based dialogue system needs to have the following four basic functions: spoken language understanding, dialogue state tracking, dialogue strategy and dialogue generation. Among them, Spoken Language Understanding (SLU), as the entrance of the whole system, is a very important technical module. Its main task is to understand the meaning of words in the context limited by the dialogue system of human-computer interaction. There are three sub-tasks of intent detection and semantic slot filling, and some systems combine do...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the above-mentioned problems in the prior art, that is, in order to solve the problem of low utilization rate of historical dialogue data in the existing multi-round spoken language understanding method, the first aspect of the present invention proposes a multi-round spoken language understanding method based on dialogue logic , the method includes:

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