Karakalpak Speech Recognition with CMU Sphinx
Mamatov Narzillo1, Samijonov Abdurashid2, Nurimov Parakhat3, Niyozmatova Nilufar4
1Mamatov Narzillo*, Scientific and Innovation Center of Information and Communication Technologies at TUIT named after Al-Kharezmi, Tashkent, Uzbekistan,
2Samijonov Abdurashid, Bauman Moscow State Technical University, Russia Federation
3Nurimov Parakhat, Scientific and Innovation Center of Information and Communication Technologies at TUIT named after Al-Kharezmi, Tashkent, Uzbekistan
4Niyozmatova Nilufar, Scientific and Innovation Center of Information and Communication Technologies at TUIT named after Al-Kharezmi, Tashkent, Uzbekistan
Manuscript received on 02 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 2446-2448 | Volume-8 Issue-10, August 2019 | Retrieval Number: J95240881019/2019©BEIESP | DOI: 10.35940/ijitee.J9074.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: One of the main problems of speech recognition systems is the diversity of natural languages. Most of the existing systems can recognize the verbal information of some natural languages. But speech recognition on many languages is not introduced into these systems due to objective or subjective reasons. Including Uzbek, Tajik, Karakalpak and other languages.
Keywords: amplitude, criteria, feature, frequency, phoneme, probability, segment, signal, speech.
Scope of the Article: Frequency Selective Surface