Ognev Ivan Vasil'evich, Doctor of engineering sciences, professor, sub-department of computing technology, National Research University "Moscow Power Engineering University" (14 Krasnokazarmennaya street, Moscow, Russia), OgnevIV@mpei.ru
Paramonov Pavel Aleksandrovich, Postgraduate student, National Research University "Moscow Power Engineering University" (14 Krasnokazarmennaya street, Moscow, Russia), email@example.com
Background. Application of hidden Markov models is based on recursive procedures featuring computational complexity. Herewith, the systems of automatic speech recognition are often required to function in real time mode, and therefore the increase of operation speed thereof is a topical problem.
Мaterials and methods. One of the approaches to solve the said problem is the realization of hardware support of computing in associative oscillometric medium. The said approach is characterized by low hardware expenditures due to the simplicity of basic cellular assemblies and functions performed thereof, as well as by high operation speed independent of the length of the sequence under analysis and of the number of conditions of hidden Markov models, due to concurrency and conveyor nature of computing.
Results. The authors suggest hardware implementation to compute the probability function of direct distribution in the medium. The researchers built a program model via Mathlab package in order to experimentally evaluate the precision of computing results in associative oscillometric medium by the example of Russian words recognition.
Conclusions. The obtained precision value of the results by the example of Russian words recognition demonstrates the efficiency of the applied model.
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