Savchenko V.V., Savchenko L.V. Two-stage algorithm of spectral analysis for automatic speech recognition systems. Izmeritel`naya Tekhnika. 2024;(7): 60-69. (In Russ.) https://doi.org/10.32446/0368-1025it.2024-7-60-69
Savchenko, V.V., Savchenko, L.V. Method for testing the stability of an autoregressive model of the vocal tract and adjusting its parameters. Meas Tech (2024). https://doi.org/10.1007/s11018-024-02359-1
Savchenko, V.V., Savchenko, L.V. A method for the asynchronous analysis of a voice source based on a two-Level autoregressive model of speech signal. Measurement Techniques, 67, 151–161 (2024). https://doi.org/10.1007/s11018-024-02330-0
Savchenko, V.V. A measure of differences in speech signals by the voice timbre. Measurement Techniques, 66, 803–812 (2024). https://doi.org/10.1007/s11018-024-02294-1
Savchenko V. V. Method for Comparison Testing of Parametric Power Spectrum Estimates: Spectral Analysis Via Time Series Synthesis. Measurement Techniques, Vol. 66, No. 6, September, 2023, р. 430-438. DOI https://doi.org/10.1007/s11018-023-02244-3
Savchenko V. V., Savchenko L. V. Suboptimal Algorithm for Measuring Pitch Frequency Using Discrete Fourier Transform of a Speech Signal // Journal of Communications Technology and Electronics, 2023, Vol. 68, No. 7, pp. 757–764. DOI: https://doi.org/10.1134/S1064226923060128
Savchenko V. V. Hybrid method of speech signals spectral analysis based on the autoregressive model and Schuster periodogram // Measurement Techniques, Vol. 66, No. 3, June, 2023. https://doi.org/10.1007/s11018-023-02211-y
Savchenko, V.V. Improving the Method for Measuring the Accuracy Indicator of a Speech Signal Autoregression Model. Meas Tech (2023). 2922. Vol. 65, No. 10, https://doi.org/10.1007/s11018-023-02150-8
Savchenko V. V. A Method For Autoregression Modeling of a Speech Signal Using the Envelope of the Schuster Periodogram as a Reference Spectral Sample // Journal of Communications Technology and Electronics, 2023, Vol. 68, No. 2, pp. 121–127. DOI: https://doi.org/10.1134/S1064226923020122
Savchenko, A.V., Savchenko, V.V. Adaptive Method for Measuring a Fundamental Tone Frequency Using a Two-Level Autoregressive Model of Speech Signals. Meas Tech. 65, 453–460 (2022). https://doi.org/10.1007/s11018-022-02104-6
Savchenko, A.V., Savchenko, V.V. Method for Measurement the Intensity of Speech Vowel Sounds Flow for Audiovisual Dialogue Information Systems. Meas Tech 65, 219–226 (2022). https://doi.org/10.1007/s11018-022-02072-x
Savchenko A.V., Savchenko V.V. Method for Automatic Online Updating of Personal Biometric Data Based on Speech Signal of the Biometric System User // Measurement Techniques, Vol. 64, No. 4, 928–935 (2022). https://doi.org/10.1007/s11018-022-02025-4
Savchenko A. V., Savchenko V. V. Real-Time Vowel Detection with Guaranteed Reliability //Journal of Communications Technology and Electronics, 2022, Vol. 67, No. 3, pp. 273–280. DOI: 10.1134/S1064226922030135.
V. V. Savchenko. Method for reduction of speech signal autoregression model for speech transmission systems on low-speed communication channels // Radioelectronics and Communications Systems. 2021. Vol. 64. No. 11. P. 592-603. https://doi.org/10.3103/S0735272721110030
V. V. Savchenko, L. V. Savchenko. Speech Signal Autoregression Modeling Based on the Discrete Fourier Transform and Scale-Invariant Measure of Information Discrimination // 1266ISSN 1064-2269, Journal of Communications Technology and Electronics, 2021, Vol. 66, No. 11, pp. 1266–1273. DOI: 10.1134/s1064226921110085
Savchenko, L.V., Savchenko, A.V. A Method of Real-Time Dynamic Measurement of a Speaker’s Emotional State from a Speech Waveform. Meas Tech, 64 (2021). https://doi.org/10.1007/s11018-021-01935-z
Savchenko, A.V., Savchenko, V.V. & Savchenko, L.V. Gain-optimized spectral distortions for pronunciation training. Optim Lett 16, 2095–2113 (2022). https://doi.org/10.1007/s11590-021-01790-5
Savchenko A. V., Savchenko V. V. Scale-Invariant Modification of COSH Distance for Measuring Speech Signal Distortions in Real-Time Mode // Radioelectronics and Communications Systems. Vol. 64 No. 6, рр. 300–309. (2021). DOI: https://doi.org/10.3103/S0735272721060030
Savchenko, V.V., Savchenko, A.V. Method for Measuring Distortions in Speech Signals during Transmission over a Communication Channel to a Biometric Identification System. Meas Tech 63, 917–925 (2021). https://doi.org/10.1007/s11018-021-01864-x
Savchenko, V.V. Acoustic Variability of Voice Signal as Factor of Information Security for Automatic Speech Recognition Systems with Tuning to User Voice. Radioelectron.Commun.Syst. 63, 532–542 (2020). https://doi.org/10.3103/S0735272720100039
Savchenko V. V., Savchenko A. V. Guaranteed Significance Level Criterion in Automatic Speech Signal Segmentation // Journal of Communications Technology and Electronics, 2020, Vol. 65, No. 11, pp. 1311–1317. DOI: 10.1134/S1064226920110157.
Savchenko A.V., Savchenko V.V., Savchenko L.V. (2020) Optimization of Gain in Symmetrized Itakura-Saito Discrimination for Pronunciation Learning. In: Kononov A., Khachay M., Kalyagin V., Pardalos P. (eds) Mathematical Optimization Theory and Operations Research. MOTOR 2020. Lecture Notes in Computer Science, vol 12095. Springer, Cham. 10.1007/978-3-030-49988-4_30.
Savchenko V.V., Savchenko А.V. A Method for the Real-Time Updating of Voice Samples in the Unified Biometric System // Measurement Techniques, Vol. 63, No. 5, P. 391-400. 2020. 10.1007/s11018-020-01800-5
Savchenko V.V., Savchenko А.V. Method for Measuring the Indicator of Acoustic Quality of Audio Recordings Prepared for Registration and Processing in the Unified Biometric System // Measurement Techniques, Vol. 62. No. 12, P. 1071-1078. DOI: 10.1007/s11018-020-01736-w
Savchenko V. V Minimum of information divergence criterion for signals with tuning to speaker voice in automatic speech recognition. Radioelectronics and Communications Systems, 2020. Vol. 63, No 1. pp. 42-54. DOI: 10.3103/S0735272720010045
Savchenko V. V., Savchenko A. V. Measurements method of the audio recordings acoustic quality indicator prepared for registration and processing in the Unified Biometric System // Measurement Techniques, 2019, vol. 62, no. 12, pp. 1071-1078. DOI: 10.1007/s11018-020-01736-w
Savchenko V.V., Savchenko L.V. Method for Measuring the Intelligibility of Speech Signals in the Kullback–Leibler Information Metric. // Measurement Techniques, 2019. Vol. 62, No. 9, рр. 832-839. DOI: 10.1007/s11018-019-01702-1
Savchenko А.V., Savchenko V.V. A Method for Measuring the Pitch Frequency of Speech Signals for the Systems of Acoustic Speech Analysis // Measurement Techniques, Vol. 62, No. 3, рр. 282-288, June, 2019. DOI: https://doi.org/10.1007/s11018-019-01617-x
Savchenko V.V., Savchenko А.V. Criterion of Significance Level for Selection of Order of Spectral Estimation of Entropy Maximum // Radioelectronics and Communications Systems, 2019, 62(5), pp. 276–286. DOI: 10.3103/S0735272719050042
Savchenko V. V. Itakura–Saito Divergence as an Element of the Information Theory of Speech Perception // Journal of Communications Technology and Electronics, 2019, Vol. 64, No. 6, pp. 590–596. DOI: 10.1134/S1064226919060093
Savchenko V. V. Criterion for Minimum of Mean Information Deviation for Distinguishing Random Signals with Similar Characteristics // Radioelectronics and Communications. 2018. Т. 61. № 9. С. 419-430. 10.3103/S0735272718090042/
Savchenko V. V. A Method of Measuring the Index of Acoustic Voice Quality Based on an Information-Theoretic Approach // Measurement Techniques April 2018, Volume 61, Issue 1, pp 79–84. https://doi.org/10.1007/s11018-018-1391-8
Savchenko V.V. Estimation of the Phonetic Speech Quality Using the Information Theoretic Approach // Journal of Communications Technology and Electronics. 2018. Vol. 63, No. 1. pp. 53-57. . DOI: 10.1134/S1064226918010126.
Savchenko V.V. Words Phonetic Decoding Method with the Suppression of Background Noise // Journal of Communications Technology and Electronics. 2017. Vol. 62, No. 7. pp. 788–793. DOI: 10.1134/S1064226917070099.
Savchenko V.V. Study of the Stationarity of Random Time Series Using the Principle of the Information-Divergence Minimum // Radiophysics and Quantum Electronics. 2017. Vol. 60. No. 1. pp. 89–96. 10.1007/s11141-017-9778-y
Savchenko V.V. Enhancement of the Noise Immunity of a Voice-Activated Robotics Control System Based on Phonetic Word Decoding Method // Journal of Communications Technology and Electronics. 2016. Vol. 61, No. 12. p. 1374 -1379. DOI: 10.1134/S1064226916120226.
Savchenko V.V., Savchenko A.V. Information Theoretic Analysis of Efficiency of the Phonetic Encoding–Decoding Method in Automatic Speech Recognition // Journal of Communications Technology and Electronics. 2016. Vol. 61. No. 4. P. 430-435. DOI: 10.1134/S1064226916040112
Savchenko V.V. The Principle of the Information-Divergence Minimum in the Problem of Spectral Analysis of the Random Time Series Under the Condition of Small Observation Samples // Radiophysics and Quantum Electronics. 2015. Vol. 58. No. 5. P. 373-379. DOI: 10.1007/s11141-015-9611-4.