Patent Document ID: 8180635
Application ID: 12347504

Base Claim:
1. A method for adapting acoustic models in a speech recognition system, the method comprising: estimating noise in a portion of a speech signal; determining a first estimated variance scaling vector using an estimated 2-order polynomial and the noise estimation, wherein the estimated 2-order polynomial represents a priori knowledge of a dependency of a variance scaling vector on noise; determining a second estimated variance scaling vector using statistics from prior portions of the speech signal; determining a variance scaling factor using the first estimated variance scaling vector and the second estimated variance scaling vector; and using the variance scaling factor to adapt an acoustic model.

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Claim 10:
10. The method of claim 1 , wherein determining the first estimated variance scaling vector further comprises computing 
 âN 2 +{circumflex over (b)}N+ĉ where N is the noise estimation, and â, {circumflex over (b)}, and ĉ are regression coefficients from a mean square estimation of a 2-order polynomial regression determined from speech signals collected under noisy conditions.