Patent ID: 11875116
Assignee: INTUIT INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 16:
17. A method of training a phrase recognition model comprising a neural network having a filter comprising a skip word setting of at least one, the method comprising:
receiving a plurality of training phrases for which corresponding known semantic meanings are available;
converting the plurality of training phrases into a vector comprising a plurality of ngrams of text;
inputting, into the phrase recognition model, the vector;
applying, using the phrase recognition model, the filter to the plurality of ngrams during execution of the neural network;
determining, based on the skip word setting, at least one ngram in the vector to be skipped to form at least one skip word;
outputting, by the neural network, an intermediate score for a set of ngrams of the plurality of ngrams that match the filter;
calculating a scalar number representing a semantic meaning of the at least one skip word;
generating based on the scalar number and the intermediate score, a final score for the set of ngrams, wherein the final score represents an estimated semantic meaning of the at least one skip word; and
comparing the estimated semantic meaning to the known semantic meanings to form a comparison; and
modifying the phrase recognition model based on the comparison between the final score and the known semantic meanings.