System and method for addressing channel mismatch through class specific transforms

Abstract

A method and system for speaker recognition and identification includes transforming features of a speaker utterance in a first condition state to match a second condition state and provide a transformed utterance. A discriminative criterion is used to generate a transform that maps an utterance to obtain a computed result. The discriminative criterion is maximized over a plurality of speakers to obtain a best transform for recognizing speech and/or identifying a speaker under the second condition state. Speech recognition and speaker identity may be determined by employing the best transform for decoding speech to reduce channel mismatch.

1 . A method for audio classification, comprising: 
 transforming features of a speaker utterance in a first condition state to match a second condition state and as a result provide a channel matched transformed utterance; and    maximizing a discriminative criterion over a plurality of speakers to obtain a best transform for audio class modeling under the second condition state.    
   
   
       2 . The method as recited in  claim 1 , further comprising employing a speaker model trained using a first channel condition provided by a first hardware type.  
   
   
       3 . The method as recited in  claim 2 , wherein the second condition state includes a second channel condition provided by a second hardware type.  
   
   
       4 . The method as recited in  claim 2 , wherein the second condition state includes a neutralized channel condition which counters effects of the first condition state.  
   
   
       5 . The method as recited in  claim 1 , wherein the system undergoes many input conditions and further comprises applying a best transform for each input condition.  
   
   
       6 . The method as recited in  claim 1 , wherein maximizing a discriminative criterion includes determining a likelihood of a speaker based on discrimination between speaker classes to identify the speaker.  
   
   
       7 . The method as recited in  claim 1 , wherein the discriminative criterion includes:  
     
       
         
           
             
               
                 
                   
                     Q 
                     1 
                   
                   = 
                   
                     
                       ∏ 
                       
                         s 
                         = 
                         1 
                       
                       S 
                     
                     ⁢ 
                     
                       Pr 
                       ⁡ 
                       
                         ( 
                         
                           
                             λ 
                             s 
                           
                           | 
                           
                             
                               Y 
                               → 
                             
                             s 
                           
                         
                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   3 
                   ) 
                 
               
             
           
         
       
       where Q 1  is a function to be optimized, and Pr(λ s |{hacek over (Y)} s ) is a posterior probability of speaker model λ s , given the speaker's channel matched transformed utterance, {right arrow over (Y)}.  
     
   
   
       8 . The method as recited in  claim 1 , further comprising decoding speech based on a selected transform.  
   
   
       9 . The method as recited in  claim 1 , further comprising transforming at least one speaker model from a first input type corresponding to the first condition state to a second input type corresponding to the second condition state by directly mapping features from the first input type to a second input type using a transform.  
   
   
       10 . The method as recited in  claim 1 , wherein maximizing includes maximizing posterior probabilities.  
   
   
       11 . A computer program product for audio classification comprising a computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the steps of: 
 transforming features of a speaker utterance in a first condition state to match a second condition state and as a result provide a channel matched transformed utterance; and    maximizing a discriminative criterion over a plurality of speakers to obtain a best transform for audio class modeling under the second condition state.    
   
   
       12 . A method for audio classification, comprising: 
 providing a plurality of transforms for decoding utterances, wherein the transforms correspond to a plurality of input types; and    applying one of the transforms to a speaker based upon the input type;    wherein the transforms are precomputed by: 
 transforming features of a speaker utterance in a first condition state to match a second condition state and as a result provide a channel matched transformed utterance; and  
 maximizing a discriminative criterion over a plurality of speakers to obtain a best transform for audio class modeling under the second condition state.  
   
   
   
       13 . The method as recited in  claim 12 , wherein the best transform is determined for each input type and applied by determining conditions under which a speaker is providing input.  
   
   
       14 . The method as recited in  claim 12 , wherein the input types include one or more of telephone handsets, channel types and microphones.  
   
   
       15 . The method as recited in  claim 12 , wherein the different condition state includes a neutralized channel condition which counters effects of the first condition state.  
   
   
       16 . The method as recited in  claim 12 , wherein maximizing a discriminative criterion includes determining a likelihood of a speaker based on discrimination between speaker classes to identify the speaker.  
   
   
       17 . The method as recited in  claim 12 , wherein the discriminative criterion includes:  
     
       
         
           
             
               
                 
                   
                     Q 
                     1 
                   
                   = 
                   
                     
                       ∏ 
                       
                         s 
                         = 
                         1 
                       
                       S 
                     
                     ⁢ 
                     
                       Pr 
                       ⁡ 
                       
                         ( 
                         
                           
                             λ 
                             s 
                           
                           | 
                           
                             
                               Y 
                               → 
                             
                             s 
                           
                         
                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   3 
                   ) 
                 
               
             
           
         
       
       where Q 1  is a function to be optimized, and Pr(λ s |{right arrow over (Y)} s ) is the posterior probability of speaker model λ s , given the speaker's channel matched transformed utterance, {right arrow over (Y)}.  
     
   
   
       18 . The method as recited in  claim 17 , further comprising decoding speech based on a selected transform.  
   
   
       19 . The method as recited in  claim 12 , wherein the transform reduces mismatch between input types.  
   
   
       20 . A computer program product for audio classification comprising a computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the steps of: 
 providing a plurality of transforms for decoding utterances, wherein the transforms correspond to a plurality of input types; and    applying one of the transforms to a speaker based upon the input type;    wherein the transforms are precomputed by: 
 transforming features of a speaker utterance in a first condition state to match a second condition state and as a result provide a channel matched transformed utterance; and  
 maximizing a discriminative criterion over a plurality of speakers to obtain a best transform for audio class modeling under the second condition state.