Model training method and device and sentence emotion recognition method and device

A model training and sentence technology, applied in the field of text processing, can solve the problem of low accuracy of emotion recognition and achieve the effect of improving accuracy

Active Publication Date: 2020-04-21
BEIJING GRIDSUM TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present application provides a model training method and device and a sentence emotion recognition method and device, so as to at least solve the technical problem of low accuracy of emotion recognition contained in sentences in the prior art

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  • Model training method and device and sentence emotion recognition method and device
  • Model training method and device and sentence emotion recognition method and device
  • Model training method and device and sentence emotion recognition method and device

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Embodiment Construction

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is an embodiment of a part of the application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0022] It should be noted that the terms "first" and "second" in the description and claims of the present application and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances such...

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Abstract

The application discloses a model training method and device, and a sentence emotion recognition method and device. Wherein, the model training method includes: obtaining text information with emotional tags, wherein the text information includes a plurality of sentences marked according to predefined emotional types, and each sentence carries an emotional tag corresponding to it; The sentence vector corresponding to each sentence, wherein, the sentence vector is a multidimensional array used to uniquely represent the corresponding sentence; the emotional mark corresponding to each sentence and its corresponding sentence vector are input to the recurrent neural network, and the neural network model is obtained by training, wherein , the neural network model is used to identify the type of sentiment in the sentence. The present application solves the technical problem of low accuracy of emotion recognition contained in sentences in the prior art.

Description

technical field [0001] The present application relates to the field of text processing, in particular, to a model training method and device, and a sentence emotion recognition method and device. Background technique [0002] The sentence input by the user usually contains the emotion of the user. In the prior art, the emotion of the sentence is mainly identified according to the emotion keywords, punctuation marks, emoticons, etc. in the sentence. However, when there are no emotional words or emotions that are difficult for machines to recognize in the analyzed sentence, the accuracy of this recognition method is relatively low, for example: you can't sing? Whether the sentence is sad, angry or happy, needs to be understood in context. In "You can't sing? It's useless!", "You can't sing? What a pity", "You can't sing? Okay, so do I. No, they sing and we play." Expressing anger, sadness, and joy respectively. However, the sentence does not contain words with clear emotiona...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/289G06F40/30G06K9/62G06N3/04
CPCG06N3/04G06F40/289G06F40/30G06F18/24
Inventor 刘粉香
Owner BEIJING GRIDSUM TECH CO LTD
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