An Algorithm for Assessing Verbal Speech Recognition based on the Coherence Function

The problem of estimating the vulnerability of the speech information of a confidential nature is currently topical. However, in the use of means of acoustic protection, i.e. in conditions of strong noise, the existing instrumental and computational methods give greater accuracy when compared with the extremely labor intensive methods of articulation.
In the paper we study the method of estimating the security of voice data based on the Pearson correlation coefficient. This ratio has poor sensitivity to the spectral properties of the acoustic signals. Therefore, the author suggests an approach to the definition of the security indicator of voice data based on the mathematical apparatus of the coher-ence function of source and noisy signals.
We propose to split the entire speech frequency range of the coherence function into separate octaves. We also offer to calculate the expectation of the coherence function components in octaves and on the basis of convolution function obtain an expression for calculating the index of the vulnerability of speech.
The proposed algorithm for determining the vulnerability index of voice data allows improving the assessment accuracy.