The effectiveness of solving applied problems in the field of speech
technologies is determined by the completeness of the use of phonetic information
obtained in the study of the properties of natural speech. The representation of a
speech signal in digital form opens up wide possibilities for its analysis and processing.
Having a digital representation of a speech signal, we can think about metrics, that is,
the parameters of this signal, with the help of which the program can recognize sounds,
words and sentences with approximately the same result that a healthy hearing aid and
a healthy human brain give.
The effectiveness of solving applied problems in the field of speech
technologies is determined by the completeness of the use of phonetic information
obtained in the study of the properties of natural speech. The representation of a
speech signal in digital form opens up wide possibilities for its analysis and processing.
Having a digital representation of a speech signal, we can think about metrics, that is,
the parameters of this signal, with the help of which the program can recognize sounds,
words and sentences with approximately the same result that a healthy hearing aid and
a healthy human brain give.
| № | Author name | position | Name of organisation |
|---|---|---|---|
| 1 | Nematov S.K. | prorector | TSTU |
| 2 | Kamolova Y.M. | scientist | TSTU |
| № | Name of reference |
|---|---|
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| 2 | R. Lawrence., B.H. Juang. Fundamental of Speech Recognition. “Prentice Hall”, 1993 |
| 3 | S. Manolakis., G. Dimitris. Applied digital signal processing: theory and practice. “MIT Press, Cambridge”, 2012, ISBN 978-0-521-11002-0 (Hardback) |
| 4 | A.V. Sergiyenko. “Digital signal processing”, 2002. 608 |
| 5 | N.V. Le., J.P. Panchenko. Pre-processing of speech signals for speech recognition system. “Young scientist”, 2011. 74 |
| 6 | I.V. Bocharov. Recognition of speech signals based on the spectral estimation method [Electronic resource]. “Researched in Russia”, 2003. 1537 |
| 7 | I.V. Bocharov., D. Yu. Akatiev “Access mode: http: // journal.ape.relarn.ru / articles”, 2003. 130 |
| 8 | A. Dorokhin., D.G. Starushko., E.E. Fedorov., V.Y. Shelepov. Segmentation of the speech signal. “Artificial intelligence”, 2000. 450 |
| 9 | N.A. Krasheninnikova. The main factors that interfere with the recognition of speech commands. “Siberian scientific bulletin”, 2011. 188 |
| 10 | Sh.K. Nematov., Y.M. Kamolova. Recognition of speech signals based on the method of spectral analysis. “Journal technical sciences and innovation”, 2021. 212 |
| 11 | G.S. Khaydarova., Y.M. Kamolova., U.A. Obidova., G.B. Yuldasheva. Rehabilitation of hearing impaired children with gaming programs after cochlear implantation. “Znanstvena misel journal. Slovenia”, 2019. 39 |