Rustam Latypov

Rustam Latypov, Evgeni Stolov

There are a few reasons for the recent increased interest in the study of local features of speech files. It is stated that many essential features of the speaker language used can appear in the form of the speech signal. The traditional instruments - short Fourier transform, wavelet transform, Hadamard transforms, autocorrelation, and the like can detect not all particular properties of the language. In this paper, we suggest a new approach to the exploration of such properties. The source signal is approximated by a new one that has its values taken from a finite set. Then we construct a new sequence of vectors of a fixed size on the base of those approximations. Examination of the distribution of the produced vectors provides a new method for a description of speech files local characteristics. Finally, the developed technique is applied to the problem of the automatic distinguishing of two known languages used in speech files. For this purpose, a simple neural net is consumed.

Albert Galiev, Shamil Ishmukhametov, Rustam Latypov et al.

In this paper, we propose a novel archival system called ARCHAIN, developed for the State archive-keeping committee of the Republic of Tatarstan (Russia). The blockchain is the primary part of the system, which stores transactions (facts of transfer of documents to the archive) in a protected form.

Rustam Latypov, Evgeni Stolov

In this paper, we present some new features describing the handwritten document as a texture. These features are based on the Radon transform. All values can be obtained easily and suit for the coarse classification of documents.

Rustam Latypov, Evgeni Stolov

A new type of watermarks for handwritten black-white documents is suggested. Insertion of the watermark in a document minimizes distortion of the latter. The method is intended for validation of handwritten records placed in blockchain database.