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Intelligent control with hierarchical stacked neural networks

  • US 10,510,000 B1
  • Filed: 06/08/2015
  • Issued: 12/17/2019
  • Est. Priority Date: 10/26/2010
  • Status: Active Grant
First Claim
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1. A method for analyzing grammar in a natural language message, comprising:

  • providing an artificial neural network having an input layer, a hidden layer, and an output layer, each comprising a plurality of neurons, and together being trained to produce an artificial neural network output from a natural language neural network input dependent on training according to a natural language grammar;

    receiving a message having a type;

    detecting an ordered set of words within the message;

    linking the set of words found within the message to a corresponding set of expected words, the set of expected words having semantic attributes;

    detecting a set of grammatical structures represented in the message, based on the type of the received message, the ordered set of words and the semantic attributes of the corresponding set of expected words;

    determining, with the artificial neural network, a degree of consistency of the set of grammatical structures represented in the message with a natural language grammar, dependent on the semantic attributes of the set of expected words according to the type of the message, and being dependent on training according to the natural language grammar, to produce a vector output of the artificial neural network representing at least a type of grammatical deviation of the set of grammatical structures represented in the message from the natural language grammar;

    at least one of storing and outputting a vector based on the output of the artificial neural network.

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