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Generic framework for large-margin MCE training in speech recognition

  • US 20080201139A1
  • Filed: 02/20/2007
  • Published: 08/21/2008
  • Est. Priority Date: 02/20/2007
  • Status: Active Grant
First Claim
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1. A method of training an acoustic model in a speech recognition system, comprising:

  • utilizing a training corpus, having training tokens, to calculate an initial acoustic model;

    computing, using the initial acoustic model, a plurality of scores for each training token with regard to a correct class and a plurality of competing classes;

    calculating a sample-adaptive window bandwidth for each training token;

    determining a value for a loss function based on the computed scores and the calculated sample-adaptive window bandwidth for each training token;

    updating parameters in the current acoustic model to create a revised acoustic model based upon the loss value; and

    outputting the revised acoustic model.

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