Method of pattern recognition using noise reduction uncertainty

• US 7,769,582 B2
• Filed: 07/25/2008
• Issued: 08/03/2010
• Est. Priority Date: 05/20/2002
• Status: Expired due to Fees

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Deng, Li, Droppo, James G., Acero, Alejandro
• Primary Examiner(s): Lerner; Martin
• Application Number:
  US12/180,260
• Publication Number:
  US 20080281591A1
• Time in Patent Office: 739 Days
• Field of Search: 704/226, 704/227, 704/228, 704/233, 704/240, 704/256, 704/256.1
• US Class Current: 704/226
• CPC Class Codes: G10L 15/20 Speech recognition techniques specially adapted for robustness in adverse environments, e.g. in noise, of stress induced speech G10L21/02 takes precedence
• CPC Class Codes: G10L 21/0208 Noise filtering

Abstract

A method and apparatus are provided for using the uncertainty of a noise-removal process during pattern recognition. In particular, noise is removed from a representation of a portion of a noisy signal to produce a representation of a cleaned signal. In the meantime, an uncertainty associated with the noise removal is computed and is used with the representation of the cleaned signal to modify a probability for a phonetic state in the recognition system. In particular embodiments, the uncertainty is used to modify a probability distribution, by increasing the variance in each Gaussian distribution by the amount equal to the estimated variance of the cleaned signal, which is used in decoding the phonetic state sequence in a pattern recognition task.

Claims

1. A method of recognizing pattern states from a noisy signal, the method comprising:

a processor removing noise from a representation of a portion of the noisy signal to produce a representation of a portion of a cleaned signal by applying a correction vector for a mixture component;

a processor identifying an uncertainty associated with removing the noise by applying a variance for a prior probability distribution of a clean signal and a variance associated with selecting the correction vector for the mixture component to a function;

a processor using the uncertainty to adjust a probability distribution to form a modified probability distribution for the mixture component; and

a processor applying the representation of a portion of the cleaned signal to the modified probability distribution to decode a pattern state.

2. The method of claim 1 wherein adjusting a probability distribution comprises adding the uncertainty to a variance of the probability distribution to form the modified probability distribution.

3. The method of claim 1 wherein the representation of a portion of the noisy signal comprises a component of a feature vector representing a frame of the noisy signal and wherein the representation of a portion of the cleaned signal comprises a component of a feature vector representing a frame of the cleaned signal.

4. The method of claim 3 wherein identifying an uncertainty comprises identifying an uncertainty associated with removing noise from the component of the feature vector for the noisy signal to form the component of the feature vector for the cleaned signal.

5. The method of claim 4 wherein using the uncertainty to adjust a probability distribution comprises using the uncertainty to adjust a probability distribution associated with the component of the feature vector.

6. The method of claim 1 wherein applying a variance for a prior probability distribution of a clean signal and a variance associated with selecting the correction vector for the mixture component to a function comprises multiplying the variances together and dividing the product by a difference between the variances.

7. The method of claim 1 wherein the variance for the prior probability distribution is determined by taking a sum over all possible mixture components.

8. The method of claim 1 wherein the variance associated with selecting the correction vector for the mixture component is calculated before receiving the representation of the portion of the noisy signal.

9. A method comprising:

a processor removing noise from a representation of a portion of a noisy signal to produce a representation of a portion of a cleaned signal by applying a correction vector for a mixture component;

a processor identifying an uncertainty, σ

_{{circumflex over (x)}m}², associated with removing the noise by applying a variance, σ

_x², for a prior probability distribution of a clean signal and a variance, Γ

_m², associated with selecting the correction vector for the mixture component to a function

${\mathrm{\sigma <br><br>}}_{{\hat{x}}_m}^2=\frac{{\mathrm{\sigma <br><br>}}_x^2<br><br>{\mathrm{\Gamma <br><br>}}_m^2}{{\mathrm{\sigma <br><br>}}_x^2-{\mathrm{\Gamma <br><br>}}_m^2};<br><br>$

a processor using the uncertainty to adjust a probability distribution to form a modified probability distribution for the mixture component; and

a processor applying the representation of a portion of the cleaned signal to the modified probability distribution to decode a pattern state.