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In this paper, a possibility of evaluating frame-based nonstationary pattern recognition methods by using Bhattacharrya distance is considered. Speech signal is used as a nonstationary signal and the comparative analysis is done through analyzing the natural speech, isolately spoken Serbian vowels and digits.
In this work, a robust recursive procedure based on WRLS algorithm with VFF and a quadratic classifier with sliding training data set for identification of non-stationary AR model of speech production system is proposed. Experimental analysis is done according to the results obtained in analyzing speech signal with voiced and mixed excitation segments. Presented experimental results justify that two...
A robust recursive procedure for identification of nonstationary AR speech model based on a quadratic classifier with a heuristic decision threshold is proposed and evaluated. A comparative experimental analysis is done through processing natural speech signal with voiced and mixed excitation segments. Obtained results show that the proposed robust procedure based on the quadratic classifier with...
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