Artificial intelligence deep learning neural network embedded control system

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...

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] At the same time, the current artificial intelligence dialogue and communication is only limited to voice assistants, and has not been widely used in daily life. It also needs artificial intelligence to learn more user behavior habits in depth, so as to control various hardware devices more intelligently, such as smart home. and other functional solutions

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