A method and system for semantic recognition

A technology of semantic recognition and to-be-recognized, applied in the field of semantic recognition, can solve problems such as student recommendation, unfavorable product promotion and use, poor experience, etc., and achieve the effect of improving acquisition efficiency, improving user experience, and improving accuracy

Inactive Publication Date: 2019-01-15
GUANGDONG XIAOTIANCAI TECH CO LTD
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Problems solved by technology

However, in the process of speaking, students often include related modal particles or repeat the same sentence
After speech recognition is performed on the speech input by the students, due to the presence of modal particles or repeated words, the program will not be able to

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  • A method and system for semantic recognition
  • A method and system for semantic recognition
  • A method and system for semantic recognition

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[0080] According to the first embodiment provided by the present invention, such as figure 1 As shown, a semantic recognition method includes:

[0081] S100 using the acquired training sample set to train the initial recognition model to obtain the recognition model;

[0082] Specifically, current machine learning methods, such as deep learning methods, rely more on massive training data than traditional methods. With the improvement of training data, new machine learning methods can continuously improve the accuracy of the machine, a feature that does not exist in traditional methods. Therefore, in order to improve the recognition accuracy of the recognition model, we need to obtain a large amount of training data to form a training sample set to train the initial recognition model and obtain the trained recognition model. The initial recognition model is a model trained based on training samples, such as neural network model, convolutional neural network model, deep neural...

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Abstract

The invention belongs to the field of semantic recognition and discloses a semantic recognition method and a system. Acquiring speech information to be recognized; inputting the speech information tobe recognized into the recognition model, removing the non-keywords and repetitive contents that do not affect the semantics in the speech information to be recognized, and generating the target speech; the target speech is semantically understood and the result of semantic recognition is obtained. The invention filters non-keywords such as modal particles and repetitive contents in the speech information to be recognized by the recognition model, solves the problem that too much redundant information in user sentences leads to semantic understanding errors, so as to improve the accuracy of semantic recognition, in order to more accurately understand the true intentions of users, better serve users, improve the user experience.

Description

technical field [0001] The invention belongs to the technical field of semantic recognition, in particular to a semantic recognition method and system. Background technique [0002] With the rapid development of smart terminals and network technology, people are more and more accustomed to using human-computer interaction scenarios in smart terminals to fulfill various needs. When doing exercises, input relevant knowledge points into the smart learning device by voice, and then you can search for the corresponding answers and knowledge explanations, so as to provide learning guidance for users. [0003] At present, in human-computer interaction scenarios, accurate understanding of semantics is the basis for making correct responses. However, in the process of speaking, students often include related modal particles or repeat the same sentence. After speech recognition is performed on the speech input by the students, due to the presence of modal particles or repeated words...

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Application Information

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IPC IPC(8): G06F16/332G06F17/27
CPCG06F40/289G06F40/30
Inventor 魏誉荧
Owner GUANGDONG XIAOTIANCAI TECH CO LTD
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