| 摘要 |
A speech recognition system may be trained with data that is independent from previous acoustics. This method of training is quicker and more cost effective than previous training methods. In training the system, after a vocabulary word is input into the system, a first set of phonemes representative of the vocabulary word is determined. Next, the first set of phonemes is compared with a second set of phonemes representative of a second vocabulary word. The first vocabulary word and the second vocabulary word are different. The comparison generates a confusability index. The confusability index for the second word is a measure of the likelihood that the second word will be mistaken as another vocabulary word, e.g., the first word, already in the system. This process may be repeated for each newly desired vocabulary word.
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