Training method and training device based on semantic recognition and terminal equipment
A technology of semantic recognition and training method, applied in the field of semantic recognition, can solve the problem of low efficiency of voice interaction, and achieve the effect of improving processing efficiency and accuracy, enhancing ease of use and practicability, and expanding the scope of recognition
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Embodiment 1
[0067] see figure 1 , is a schematic diagram of the implementation flow of the semantic recognition-based training method provided by the embodiment of the present invention. The method is applied to intelligent terminal devices capable of voice interaction, such as robots, mobile phones, computers, tablet computers, or smart home products. The smart terminal device judges the operation instruction generated by voice recognition, obtains the intention of the operation instruction, and executes the action of the corresponding operation instruction.
[0068] As shown, the method includes the following steps:
[0069] Step S101, preprocessing the preset operation instruction corpus to obtain a training set based on the first operation instruction text.
[0070] In this embodiment, the preset operating instruction corpus may be pre-configured corpus of smart terminal equipment, including colloquial operating instruction corpus without keywords. The operating instruction corpus ...
Embodiment 2
[0102] refer to figure 2 , is a schematic diagram of the implementation flow of the semantic recognition-based training method provided by another embodiment of the present invention. This embodiment further verifies the prediction model of the first embodiment for the operation instruction text after speech recognition.
[0103] As shown, the method includes:
[0104] Step S201, receiving operation instruction information generated through voice recognition.
[0105] In this embodiment, the input voice is recognized by the voice recognition device, and the corresponding operation instruction information is acquired. The operation instruction information generated according to the input voice includes content such as stop words or time generated by a pause in the middle.
[0106] Step S202, performing formatting processing on the operation instruction information, and acquiring a second operation instruction text corresponding to the operation instruction information.
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Embodiment 3
[0118] see image 3 , is a schematic diagram of a training device based on semantic recognition provided in Embodiment 3 of the present invention. For ease of description, only parts related to the embodiment of the present invention are shown.
[0119] The training device 300 based on semantic recognition includes:
[0120] The processing unit 31 is configured to preprocess the preset operation instruction corpus, and obtain a training set based on the first operation instruction text;
[0121] The training unit 32 is used to perform one-level training on the preprocessed operation instruction corpus, and obtain an intermediate vector model based on the operation instruction corpus;
[0122] Establishing a mapping unit 33, configured to establish a mapping relationship between the intermediate vector model and the training set;
[0123] The model building unit 34 is configured to perform secondary training on the intermediate vector model corresponding to the training set a...
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