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Martinek, Radek, Kahankova, Radana, Bilik, Petr, Nedoma, Jan, Fajkus, Marcel, Blaha, Petr.  2018.  Speech Quality Assessment Based on Virtual Instrumentation. Proceedings of the 10th International Conference on Computer Modeling and Simulation. :49–53.

This paper introduces a program for objective and subjective evaluation of speech quality. Using this environment, a lot of speech recordings and various indoor and outdoor noises were processed. As a subjective speech evaluation method, the Dynamic time warping (DTW) method was selected, with PARCOR coefficients being chosen as symptom vectors. For the filtration of the noise in the recording, adaptive filtering based on LMS and RLS algorithms was used and the performance of the adaptive filtering was assessed. Similarity ranged from 70% to 95% for both algorithms. In terms of signal to noise ratio, the RLS algorithm ranged from 36 dB to 42 dB, while the LMS algorithm only varied from 20 dB to 29 dB.