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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Resumo

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.

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Sobre autores

V. Savchenko

Editorial office of the journal “Radio Engineering and Electronics”

Autor responsável pela correspondência
Email: vvsavchenko@yandex.ru
Rússia, Mokhovaya St., 11, bldg. 7, Moscow, 125009

L. Savchenko

National Research University Higher School of Economics

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

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2. Fig. 1. Estimation of the envelope of the SPM (3) signal of the vowel phoneme “a” with the SNR q2 equal to 0 (1), 10 (2) and 20 dB (3).

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3. Fig. 2. Estimates of the KLP of the phoneme “a” signal with the q2 SNR equal to 0 (1), 10 (2) and 20 dB (3) in comparison with the KLP vector in the absence of noise (dotted line).

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4. Fig. 3. Pulse response (5) of the forming filter (4) at SNR q2 equal to 0 (1), 10 (2) and 20 dB (3).

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5. Fig. 4. Corrected impulse response (6) at c = 0.01 (1), 0.03 (2) and 0.05 (3) for the case of equal SNR q2 = 0 dB in comparison with the impulse response (5) in the absence of correction (dotted line).

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6. Fig. 5. The envelope of the SPM (3) of the synthesized voice signal at c = 0.01 (1), 0.03 (2) and 0.05 (3) for the case of equal SNR q2 = 0 dB and in the absence of correction (dotted line).

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7. Fig. 6. Fragments of the synthesized signal of the vowel phoneme “a" in c = 0.01 (1), 0.03 (2) and 0.05 (3) for the case of equal SNR q2 = 0 dB and in the absence of correction (dotted line).

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8. 7. Schuster periodogram (10) of the vowel phoneme “a” signal synthesized according to the AR model (2) at c = -0.06 (solid curve) and c = 0 (dotted line).

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9. 8. Schuster periodogram (10) of the signal of the fricative sound of speech “w" synthesized according to the AR model (2) at c = 0.06 (solid curve) and c = 0 (dotted line).

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