Model training method for unspecified person alone word, recognition system and recognition method
A non-specific person, recognition method technology, applied in the field of speech recognition, can solve the problems of low recognition rate and large amount of calculation, and achieve the effect of improving the recognition rate, reducing the amount of calculation, and reducing the amount of calculation.
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[0050] The present invention utilizes a plurality of training models obtained based on the DTW algorithm for non-specific isolated words to merge to obtain a central training model corresponding to the isolated word, so that each isolated word has only one central training model at last, so that in the model matching step, according to the input voice When the eigenvalues of the data are matched with the training models of all isolated words, each isolated word only needs to be matched with one central training model, which greatly reduces the number of matching operations and reduces the amount of calculation during the matching operation.
[0051] As shown in Figure 3, the non-specific person isolated word model training method of the present invention specifically includes the following steps:
[0052] Step 31, using the DTW algorithm to obtain multiple training models of a non-specific isolated word;
[0053] Step 32, use the DTW algorithm to carry out two-two matching t...
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