Intention recognition model training method and device and electronic equipment

A technology for identifying models and training methods, applied in neural learning methods, biological neural network models, electrical digital data processing, etc. Improve user experience, improve accuracy, improve the effect of technical effects

Active Publication Date: 2020-05-12
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The intention recognition model training method, device and electronic equipment proposed by this application are used to solve the related technologies. When training the intention recognition model based on the deep neural network, if the scale of t

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  • Intention recognition model training method and device and electronic equipment
  • Intention recognition model training method and device and electronic equipment
  • Intention recognition model training method and device and electronic equipment

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Embodiment Construction

[0016] Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0017] The embodiment of the present application is aimed at related technologies, when training an intent recognition model based on a deep neural network, if the training corpus is small, due to insufficient training data, it is difficult for the deep neural network model to accurately model the semantics of the dialogue, thus The accuracy of intent recognition is ...

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Abstract

The invention provides an intention recognition model training method and device and electronic equipment, and relates to the technical field of artificial intelligence. The method comprises the following steps: determining slot characteristics corresponding to each intention in a training sample set; determining a first intention vector of each sample according to the matching degree of each sample and the slot feature corresponding to each intention; utilizing a first preset encoder to encode the word segmentation vector, the part-of-speech vector and the entity vector corresponding to eachsample, and determining a second intention vector corresponding to each sample; utilizing a preset decoder to decode the first intention vector and the second intention vector corresponding to each sample, and determining a prediction intention corresponding to each sample; and updating a first preset encoder and a preset decoder according to the difference between the prediction intention and thelabeling intention corresponding to each sample. Therefore, through the intention recognition model training method, the accuracy of intention recognition of the deep neural network model under a small-scale training sample is improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to the field of artificial intelligence technology, and proposes an intention recognition model training method, device and electronic equipment. Background technique [0002] In the process of human-computer dialogue interaction, the machine needs to understand the intention of the dialogue sentence. At present, the classification model based on deep neural network is usually used to classify the intention, so as to obtain the intention of a dialogue. [0003] In related technologies, in order to ensure the accuracy of the classification model, it is usually necessary to train the intent classification model with more than hundreds of thousands of labeled training corpora. However, in practical applications, due to the high cost of labeled data, there are usually only tens of thousands or even hundreds of labeled training data in the cold start phase. On a small-scale ...

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Application Information

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IPC IPC(8): G06F16/35G06F16/36G06F40/30G06F40/295G06N3/04G06N3/08
CPCG06F16/35G06N3/08G06F16/36G06N3/045
Inventor 张红阳韩磊孙叔琦孙珂李婷婷
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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