Artificial intelligence deep learning neural network embedded control system

An embedded control and deep learning technology, which is applied in the transmission system, signal transmission system, digital transmission system, etc., can solve problems such as lack of large-scale application, incoherent dialogue, and language congestion, so as to realize offline speech recognition and improve operation Effects of speed, low power consumption

Inactive Publication Date: 2018-05-08
四川声达创新科技有限公司
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

If the transfer of the situational state between the dialogue sentences is not considered, the dialogue will have incoherent meaning and language congestion during the dialogue process, which will not increase the number of rounds of dialogue between the user and the artificial intelligence dialogue system, and reduce the user's willingness to use
[0004] A

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  • Artificial intelligence deep learning neural network embedded control system

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Embodiment Construction

[0018] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0019] The invention provides an artificial intelligence deep learning neural network embedded control system, such as figure 1 As shown, it includes a control center and an intelligent external device 11, the control center includes a microprocessor 5, a voice recognition unit 3, and the voice recognition unit 3 includes a voice collector 1, a semantic parser 2, and the voice collector 1 The output end of the semantic parser 2 is electrically connected to the input end of the semantic parser 2, the output end of the semantic parser 2 is electrically connected to the input end of the command lexicon 4, and the output end of the command lexicon 4 is electrically connected to the microprocessor 5 the input terminal;

[0020] The control center also includes an infrared remote control unit 6. The infr...

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Abstract

The invention discloses an artificial intelligence deep learning neural network embedded control system, comprising a control center and a smart external device. The control center comprises a microprocessor and a voice recognition unit. The voice recognition unit comprises a voice collector and a semantic analyzer. An output end of the voice collector is electrically connected with an input end of the semantic analyzer. The output end of the semantic analyzer is electrically connected with the input end of a command word library. The output end of the command word library is electrically connected with the input end of the microprocessor. The control center also comprises an infrared remote control unit. The infrared remote control unit comprises an infrared signal receiver and an infrared signal code library. The output end of the infrared signal receiver is electrically connected with the input end of the infrared signal code library. The infrared signal code library is intercommunicated with an internal memory unit through a dedicated channel. The output end of the infrared signal code library is electrically connected with the input end of the microprocessor. According to thesystem, an offline voice command word library can be stored in the internal or eternal memory unit, thereby realizing offline voice recognition.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to an artificial intelligence deep learning neural network embedded control system. Background technique [0002] Today's society has entered an era of rapid technological change. Among them, one of the most obvious signs is the influx of high-tech products into the consumer market. They bring great convenience and enjoyment to people's work, life, communication, study and transportation. On the other hand, the popularity of high-tech products also brings great challenges to the improvement of high-tech products themselves, such as artificial intelligence control systems. [0003] Most of the current artificial intelligence control systems focus on processing single-loop question-and-answer dialogues, and do not consider the transfer of situational states between dialogue utterances, and cannot generate robot dialogue strategies based on the transfer of situational...

Claims

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Application Information

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IPC IPC(8): H04L12/28G10L15/18G10L15/22G08C23/04
CPCG08C23/04G10L15/1822G10L15/22G10L2015/223H04L12/282H04L2012/2841H04L2012/285
Inventor 蒋川宁程丹赵飞洪
Owner 四川声达创新科技有限公司
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