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Recurrent conditional random fields

  • US 9,239,828 B2
  • Filed: 03/07/2014
  • Issued: 01/19/2016
  • Est. Priority Date: 12/05/2013
  • Status: Active Grant
First Claim
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1. A language understanding (LU) system, comprising:

  • a computing device; and

    a computer program having program modules executable by the computing device, the computing device being directed by the program modules of the computer program to,receive feature values corresponding a sequence of words,generate semantic labels for words in the sequence of words, said semantic label generation comprising using a recurrent conditional random field (R-CRF) comprising,a recurrent neural network (RNN) portion which generates RNN activation layer activations data that is indicative of a semantic label for a word, the RNN receiving feature values associated with a word in the sequence of words and outputting RNN activation layer activations data that is indicative of a semantic label, anda conditional random field (CRF) portion which takes as input the RNN activation layer activations data output from the RNN for one or more words in the sequence of words and outputs label data that is indicative of a separate semantic label that is to be assigned to each of the one or more words in the sequence of words associated with the RNN activation layer activations data, andassign each semantic label corresponding to the data output by the CRF portion of the R-CRF to the appropriate one said one or more words in the sequence of words.

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