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Model training method, device, equipment and storage medium

A technology for training models and training samples. Applied in the field of training models, it can solve problems such as difficulty in reusing data, and achieve the effect of reducing costs and improving the effect of intent recognition.

Active Publication Date: 2020-09-18
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In this way, when faced with new application scenarios, it is difficult to reuse the data of the previously established human-machine dialogue robot

Method used

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  • Model training method, device, equipment and storage medium
  • Model training method, device, equipment and storage medium
  • Model training method, device, equipment and storage medium

Examples

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Embodiment Construction

[0019] 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.

[0020] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0021] figure 1 An exemplary system architecture 100 is shown to which emb...

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Abstract

The invention discloses a model training method, a device, equipment and a storage medium and relates to the technical field of natural language processing and deep learning. According to the specificimplementation scheme, the method comprises the steps of obtaining a first training sample set and a second training sample set; predicting the first sample data by using a first intention recognition model, and determining confidence coefficients corresponding to the prediction intentions; determining a third training sample set according to the first labeling intention, the confidence coefficient corresponding to each prediction intention, the second sample data and the corresponding second labeling intention; and training a second intention recognition model according to the third trainingsample set. According to the implementation mode, historical data used for establishing the man-machine conversation robot can be fully utilized, the cost of newly establishing the man-machine conversation robot is reduced, and the intention recognition effect of the newly established man-machine conversation robot is improved under the condition of a small number of labeled samples.

Description

technical field [0001] The present application relates to the field of computer technology, specifically to the field of natural language processing and the field of deep learning technology, especially to methods, devices, equipment and storage media for training models. Background technique [0002] Intent recognition is one of the core functions of human-machine dialogue robots, and it is usually implemented using an intent recognition model. The effect of the intent recognition model depends heavily on the quantity and quality of training data. The larger the number of samples in the training data and the higher the annotation quality, the better the effect of the obtained intent recognition model. Manually labeled intent dialogue samples have high data quality, but it is difficult to scale up due to the high cost of labeling. [0003] With the rise of human-computer dialogue robots, various human-computer dialogue robots will be established for different applications,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/30G06F16/332G06K9/62
CPCG06F40/30G06F16/3329G06F18/214G06F18/24
Inventor 韩磊张红阳孙叔琦孙珂李婷婷
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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