Speech Signal Autoregression Modeling Based on the Discrete Fourier Transform and Scale-Invariant Measure of Information Discrimination
In this paper, we consider the problem of autoregressive modeling of a speech signal according to the data of its discrete Fourier transform on intervals of one speech frame (several milliseconds). Based on the information-theoretic approach, a novel method, in which two computational procedures, na...
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| Veröffentlicht in: | Journal of communications technology & electronics 2021-11, Vol.66 (11), p.1266-1273 |
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| container_issue | 11 |
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| container_title | Journal of communications technology & electronics |
| container_volume | 66 |
| creator | Savchenko, V. V. Savchenko, L. V. |
| description | In this paper, we consider the problem of autoregressive modeling of a speech signal according to the data of its discrete Fourier transform on intervals of one speech frame (several milliseconds). Based on the information-theoretic approach, a novel method, in which two computational procedures, namely, iterative optimization of autoregressive parameters and their automatic amplitude scaling are separated from each other was developed. A full-scale experiment was set up and carried out. The main advantage of the new method in comparison with its known analogs is shown to be the extremely high rate of convergence of iterations to the optimal solution. |
| doi_str_mv | 10.1134/S1064226921110085 |
| format | Article |
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The main advantage of the new method in comparison with its known analogs is shown to be the extremely high rate of convergence of iterations to the optimal solution.</description><subject>Autoregressive models</subject><subject>Communications Engineering</subject><subject>Engineering</subject><subject>Fourier transforms</subject><subject>Information theory</subject><subject>Iterative methods</subject><subject>Networks</subject><subject>Optimization</subject><subject>Speech</subject><subject>Theory and Methods of Signal Processing</subject><issn>1064-2269</issn><issn>1555-6557</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>N95</sourceid><recordid>eNp1kc9u1DAQxiMEEqXwANwscUIixX9ir3NcWgortUIi5Rx57XHW1a6zeBwET8Br4zRIsELIB3tmft_I30xVvWT0gjHRvO0YVQ3nquWMMUq1fFSdMSllraRcPS7vUq7n-tPqGeI9paJVVJxVP7sjgN2RLgzR7Ml6ymOCIQFiGCO5HR3sQxzIO4PgSMnkHZCrgDZBBnI9TilAInfJRPRjOhATHems2UO9id9MCiZmcgsGpwRk9GQTZ8rkufdDl3AI8SF8Xj3xZo_w4vd9Xn25fn93-bG--fRhc7m-qW3DVa6t8o2xWjfQ0NYLt7XOUK41tNxYq7SzciWNN8y2LVgtnFAr513htnwrLBfn1aul7zGNXyfA3N8XE8U69ly2mlHGdVOoi4UaipU-lF_nZGw5Dg7BjhF8KPm10lxLxVtRBK9PBIXJ8D0PZkLsN93nU_bNX-x2whDncUcMwy7jIjnB2YLbNCIm8P2xjM2kHz2j_bz7_p_dFw1fNFjYOED64_L_ol9Jz7JA</recordid><startdate>20211101</startdate><enddate>20211101</enddate><creator>Savchenko, V. 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| language | eng |
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| source | Springer Nature - Complete Springer Journals |
| subjects | Autoregressive models Communications Engineering Engineering Fourier transforms Information theory Iterative methods Networks Optimization Speech Theory and Methods of Signal Processing |
| title | Speech Signal Autoregression Modeling Based on the Discrete Fourier Transform and Scale-Invariant Measure of Information Discrimination |
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