| Abstract [eng] |
The accuracy of speech recognition system depends on characteristics of employed speech recognition features and classifier. Evaluating the accuracy of speech recognition system in ordinary way, the error of speech recognition system has to be calculated for each type of explored feature system and each type of classifier. The amount of such calculations can be reduced if the quality of explored feature system is estimated. Accordingly, the researches were made for quality estimation of speech recognition features. The proposed method for quality estimation of speech recognition features is based on three metrics usage. It was demonstrated, that the proposed method describes the quality of speech recognition features in Euclidean space and reduces the calculations of quality estimation of speech recognition systems. Demonstrated, that algorithm complexity of method for quality estimation of speech recognition features is O(2Rlog2R), while algorithm complexity of dynamic time warping recognition system is O(R^2), where R is vectors number of speech pattern references. The results of experimental researches confirmed the correctness of the proposed method for quality estimation of speech recognition features. |
