Ex parte TAKEBAYASHI et al. - Page 2

               Appeal No. 1997-4121                                                                                                    
               Application No. 08/427,272                                                                                              

               employed in such speech recognition systems is typically prepared by using the word feature vectors                     

               obtained by using specific word boundaries and a specific noise level.  Therefore, when the conventional                

               dictionary is used with the word spotting method, matching with the word feature vector obtained from an                

               unfixed word boundary for a speech mixed with noise having a low signal/noise ratio, as in a practical                  

               environment, causes some recognition errors.  The instant invention is directed to obtaining a high                     

               recognition rate even in noisy environments.  It also includes an effective learning system for word spotting           

               methods of speech recognition.                                                                                          

                       Representative independent claim 1 is reproduced as follows:                                                    

                               1.  An apparatus for time series signal recognition, comprising:                                        
                               means for inputting signal patterns for time series signals to be recognized;                           
                               means for recognizing the time series signals according to a word spotting scheme using                 
               continuous pattern matching, including;                                                                                 
                               means for extracting a plurality of candidate feature vectors for characterizing an                     
                       individual time series signal from the signal patterns;                                                         
                               recognition dictionary means for storing reference patterns with which the individual                   
               time series signals are matched;                                                                                        
                               means for calculating similarity values for each of the extracted candidate feature                     
                       vectors and the reference patterns;                                                                             
                               means for determining a recognition result by selecting one of said stored reference                    
               patterns that matches with one of the candidate feature vectors by the continuous pattern matching                      
               for which the similarity value calculated by the calculating means is greater than a prescribed                         
               threshold value; and                                                                                                    
                               means for learning new reference patterns to be stored in the recognition dictionary                    
               means, including:                                                                                                       
                               means for mixing speech patterns with noise database patterns representing                              
               background noises, to form signal patterns for learning, and supplying the signal patterns for learning to the          
               recognizing means;                                                                                                      
                               means for extracting feature vectors for learning from the recognition results and the                  


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