Linear prediction coefficients correction method for digital speech processing systems with data compression based on the autoregressive model of a voice signal

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Abstract

The problem of distortion of the autoregressive model of the voice signal under the influence of additive background noise in digital speech processing systems with data compression based on linear prediction is considered. In the frequency domain, these distortions are observed in the weakening of the main formants responsible for the intelligibility of the speaker’s speech. To compensate for formant attenuation, it is proposed to modify the parameters of the autoregressive model (linear prediction coefficients) using the impulse response of a recursive shaping filter. Along with the amplitude amplification of the formants, their frequencies remain unchanged to make the speaker’s voice recognizable. The effectiveness of the method was studied experimentally using specially developed software. Based on the experimental results, conclusions were drawn about a significant increase in the relative level of formants in the power spectrum of the corrected voice signal.

About the authors

V. V. Savchenko

Editorial office of the journal “Radio Engineering and Electronics”

Author for correspondence.
Email: vvsavchenko@yandex.ru
Russian Federation, Mokhovaya St., 11, bldg. 7, Moscow, 125009

L. V. Savchenko

National Research University Higher School of Economics

Email: vvsavchenko@yandex.ru
Russian Federation, B. Pecherskaya St., 25, Nizhny Novgorod, 603155

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