Sentence segmentation method, device and equipment based on natural language, and storage medium

Abstract

The invention relates to the technical field of big data, and discloses a sentence segmentation method, device and equipment based on a natural language and a storage medium, which are used for segmenting sentences by adopting a natural language processing algorithm so as to improve the sentence segmentation flexibility and accuracy. The sentence segmentation method based on the natural language comprises the steps of obtaining to-be-processed voice data from a first service scene, or obtaining to-be-processed text data from a second service scene; when to-be-processed voice data is acquired, inputting the to-be-processed voice data into a preset voice recognition model, performing feature screening and sentence segmentation in combination with a natural language processing algorithm, and generating target text sentence segmentation data; when to-be-processed text data is obtained, inputting the to-be-processed text data into a pre-trained text sentence segmentation model for feature screening and sentence segmentation, and generating target text sentence segmentation data; and generating target response data according to the target text sentence segmentation data and the scene configuration. In addition, the invention also relates to a blockchain technology, and the to-be-processed voice data can be stored in the blockchain.

Description

technical field [0001] The present invention relates to the technical field of natural language processing, in particular to a sentence segmentation method, device, equipment and storage medium based on natural language. Background technique [0002] With the continuous development and application of artificial intelligence technology, there are more and more robot service scene applications, and human-computer interaction will become a common technology in the new era. For the customer service industry, whether it is telephone sales or customer service centers, intelligent customer service robots can not only help companies save costs and reduce labor costs, but also greatly improve work efficiency. They are the best assistants for customer service personnel. Segmenting user utterances is the first step in text processing for customer service robots. Sentence segmentation will affect the accuracy of all subsequent interactive modules, thus affecting the performance of custo...

AI Technical Summary

Problems solved by technology

At present, most of the customer service robot sentence segmentation modules on the market use the voice endpoint detection technology to perform sentence segmentation, that is, combine the frequency domain, spectral entropy, fundamental frequency and other voice features to detect the starting point and ending point of the actual voice segment from the continuous audio signal, and then from the Sentence at the end point, or determine the sentence according to the length of the pause between the end point and the next start point, but the sentence segmentation method of the speech endpoint detection technology will have the problem of identifying the sentence start point and the sentence end point, thereby reducing the accuracy of sentence segmentation

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