Linguistic and Statistical Analysis of Audio Texts
DOI:
https://doi.org/10.55544/jrasb.4.3.6Keywords:
linguostatistical analysis, phonetic change, morphological model, syntactic structure, natural language processing (NLP), artificial intelligence, automatic transcriptionAbstract
This article provides an in-depth analysis of the phonetic, morphological, and syntactic features of Uzbek audio texts based on linguostatistical analysis. The study integrates modern information and communication technologies, particularly natural language processing (NLP), speech technologies, and corpus linguistics methods. The article scientifically examines phonetic analysis (elision, assimilation, coarticulation), morphological modeling (word forms, affixes), and syntactic structures (asyndetic sentences, introductory words) conducted on audio texts. The Praat software was used for experimental analysis, while the uzbekcorpus.uz platform was utilized for statistical modeling. Based on the research results, practical recommendations are provided for creating automatic transcription, machine translation, ASR, and NLP systems for the Uzbek language. This article contributes to new scientific directions within the framework of integrating linguistics and artificial intelligence.
Downloads
References
Urazaliyeva, M. (2024). Audiomatnlar konteksti va ularning tipologiyasi. Yangi O‘zbekiston tilshunosligi jurnali, 3(2), 191-198.
Jurafsky, D., & Martin, J. H. (2021). Speech and language processing (3rd ed.). Pearson. — 230 b.
Zipf, G. K. (1949). Human behavior and the principle of least effort. Cambridge, MA: Addison-Wesley. — 67 b
Boersma, P., & Weenink, D. (2001). Praat: doing phonetics by computer [Computer program]. Version 6.0.37. URL: http://www.praat.org
Bybee, J. L. (1985). Morphology: A Study of the Relation Between Meaning and Form. Amsterdam: John Benjamins. — 378 b.
Givón, T. (2001). Syntax: An Introduction. Vol. I. Amsterdam: John Benjamins Publishing. — 424 b.
Chomsky, N. (1957). Syntactic Structures. The Hague: Mouton. — 116 b.
Givón, T. (2001). Syntax: An Introduction. Vol. I. Amsterdam: John Benjamins Publishing. — 424 b
Hinton, G., Deng, L., Yu, D., et al. (2012). Deep Neural Networks for Acoustic Modeling in Speech Recognition. IEEE Signal Processing Magazine, 29(6), 82–97.
Abdurakhmonova, N., Tuliyev, U., & Gatiatullin, A. (2021). Linguistic functionality of Uzbek Electron Corpus: Uzbekcorpus. uz. In International Conference on Information Science and Communications Technologies: Applications, Trends and Opportunities, ICISCT 2021.
Agostini, A., Usmanov, T., Khamdamov, U., Abdurakhmonova, N., & Mamasaidov, M. (2021, January). Uzwordnet: A lexical-semantic database for the uzbek language. In Proceedings of the 11th Global Wordnet conference (pp. 8-19).
Abdurakhmonova, N., Alisher, I., & Toirova, G. (2022, September). Applying Web Crawler Technologies for Compiling Parallel Corpora as one Stage of Natural Language Processing. In 2022 7th International Conference on Computer Science and Engineering (UBMK) (pp. 73-75). IEEE.
Abdurakhmonova, N., & Ismailov, A. S. (2022). APPLYING WEB CRAWLER TECHNOLOGIES FOR COMPILING PARALLEL CORPORA AS ONE STAGE OF NATURAL LANGUAGE PROCESSING. In СОВРЕМЕННАЯ ФИЛОЛОГИЯ. СОЦИАЛЬНАЯ И НАЦИОНАЛЬНАЯ ВАРИАТИВНОСТЬ ЯЗЫКА И ЛИТЕРАТУРЫ (pp. 22-27).
Abduraxmonova, N., & Abduvaxobov, G. I. (2021). O ‘quv lug ‘atini tuzishning nazariy metodologik asoslari. СЎЗ САНЪАТИ ХАЛҚАРО ЖУРНАЛИ, 103.
Sulevmanov, D., Gatiatullin, A., Prokopyev, N., & Abdurakhmonova, N. (2020, November). Turkic morpheme web portal as a platform for turkology research. In 2020 International Conference on Information Science and Communications Technologies (ICISCT) (pp. 1-5). IEEE.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Urazaliyeva Mavluda Yangiboyevna

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.








