METHOD FOR REDUCING COMPUTATIONAL QUANTITY AMOUNT UTTERRANCE VERIFICATION USING ANTI-PHONEME MODEL

摘要

Disclosed is a method for reducing computational quantity amount utterance verification using an anti-phoneme model in order to reduce a scenario error due to a wrong recognition in a speech recognition application system. In the method, a plurality of phonemes are arranged. Distances between the phonemes are measured using, a Bhattacharyya's distance manner. The phonemes are integrated from a phoneme having the greatest degree of similarity, one by one, to perform an integrated layer clustering. Anti-phoneme model aggregates are classified into nine classes by the integrated layer clustering. Each of the nine classes has a similar phoneme. A degree of similarity with respect to an uttered phoneme based on the anti-phoneme model aggregates which are classified into the nine classes is calculated during an utterance verification.