INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCHERS
ISSN: 3030-332X Impact factor: 8,293
Volume 11, issue 1, April 2025
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279
Nurullayev Mirzabek Qobil ugli
Teacher of the Department of Applied Sciences
of English at Navoi State University
EVELOPING LANGUAGE TEACHING PROGRAMS BASED ON COMPUTER
LINGUISTICS: A COMPARATIVE ANALYSIS OF UZBEK AND ENGLISH
Аннотация:
Данное исследование посвящено
анализу возможностей
создания
интерактивных программ обучения узбекскому и английскому языкам с использованием
инструментов
компьютерной
лингвистики.
Сравниваются
морфологические,
синтаксические и семантические особенности обоих языков, на основе чего предлагается
модель эффективной языковой обучающей системы. Также рассматривается применение
искусственного интеллекта, корпусной лингвистики и технологий автоматического
анализа в образовании.
Ключевые слова:
компьютерная лингвистика, обучение языкам, узбекский язык,
английский язык, сравнительный анализ, искусственный интеллект, образовательные
технологии, интерактивная программа
Annotation:
This study focuses on developing interactive language learning programs for Uzbek
and English using computer linguistics tools. The research involves a comparative analysis of
morphological, syntactic, and semantic features of both languages to design an effective
educational system. It also explores the integration of artificial intelligence, corpus linguistics,
and automated analysis technologies in language education.
Keywords:
computational linguistics, language learning, Uzbek language, English language,
comparative analysis, artificial intelligence, educational technologies, interactive program.
Introduction
The development of modern technologies also has a direct impact on the field of Education.
In particular, computer linguistics (or Computational Linguistics) has become an innovative
direction of Language Teaching. Although today there are many digital applications for Learning
English, there are still not enough quality and effective tools aimed at the Uzbek language. This
article examines the possibilities of developing language teaching programs using computer
linguistics tools based on morphological, syntactic and semantic comparative analysis of Uzbek
and English.
Computer linguistics is an interdisciplinary direction that processes natural languages
through artificial intelligence, database, and algorithmic approaches. It performs many functions
such as language analysis, translation, automatic correction, speech recognition, written speech
to voice, semantic analysis. These technologies provide an important foundation in the
development of interactive Language Teaching Systems.
Comparative analysis of Uzbek and English
Morphological features:
INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCHERS
ISSN: 3030-332X Impact factor: 8,293
Volume 11, issue 1, April 2025
https://wordlyknowledge.uz/index.php/IJSR
worldly knowledge
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280
English has an analytic structure, with words mostly applied in strict order, and
grammatical meaning expressed through more auxiliary words. Uzbek, on the other hand, is an
agglutinative language, in which grammatical meaning is expressed through suffixes. Therefore,
the development of morphological analyzers for the Uzbek language is more complex.
Syntactic aspects:
In English, the SVO (Subject-Verb-Object) word order is stricter, while in Uzbek it is freer.
This requires a special approach to developing a syntactic module in machine translation and
automatic analysis systems.
Semantic analysis:
The synonymous, metaphorical, phrase richness of both languages is a challenge for
computer language. Therefore, it is important to create a context-based semantic model through
Corpus Linguistics tools.
Computer linguistics options for language teaching programs
In language teaching programs, the following modules can be developed using computer
linguistics:
Automatic pronunciation analysis and Correction
Creating text-based grammar exercises
Constructing tests based on semantic context
Language learning with voice commands
Real - time translation and contextual analysis.
Automatic Pronunciation Analysis and Correction (APAC) is an emerging field within
computer-assisted language learning (CALL) and speech processing technologies. It focuses on
the use of artificial intelligence (AI), machine learning (ML), and natural language processing
(NLP) to evaluate and improve learners’ pronunciation in real-time. This technology has become
increasingly relevant in foreign language education, particularly in improving fluency and
intelligibility among second-language learners. This paper explores the fundamental techniques,
models, and applications used in APAC systems, along with their challenges and potential for
future development.
Text-based grammar exercises are a vital component of language education, focusing on
enhancing learners’ understanding of grammatical structures through contextually rich materials.
Unlike isolated sentence drills, these exercises use authentic or semi-authentic texts to help
students recognize and apply grammatical rules in meaningful contexts. This approach
strengthens both receptive and productive language skills. The paper explores principles,
methods, and digital tools used to develop effective text-based grammar exercises.
Semantic-context-based tests focus on evaluating language learners’ comprehension and
use of words, phrases, and grammar structures by embedding them within meaningful and
realistic contexts. Unlike decontextualized testing, which often assesses isolated knowledge,
INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCHERS
ISSN: 3030-332X Impact factor: 8,293
Volume 11, issue 1, April 2025
https://wordlyknowledge.uz/index.php/IJSR
worldly knowledge
Index:
google scholar, research gate, research bib, zenodo, open aire.
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281
context-based assessments emphasize deeper understanding and cognitive language processing.
This paper discusses the principles, types, and methods for constructing tests grounded in
semantic context, particularly useful in language teaching and assessment.
Voice command technology, integrated into smart devices and applications, is reshaping
language education by enabling hands-free, interactive, and personalized learning experiences.
Utilizing voice-based interactions for vocabulary acquisition, pronunciation practice,
conversational skills, and grammar reinforcement aligns with modern trends in mobile and
ubiquitous learning. This paper explores how voice commands enhance language learning, their
pedagogical value, underlying technologies, and best practices for implementation.
Real-time translation has moved beyond simple word-for-word substitution, thanks to
advancements in neural machine translation (NMT) and artificial intelligence. Today's systems
integrate contextual analysis to improve accuracy, tone, idiomatic usage, and cultural
appropriateness. This paper explores the technologies, linguistic strategies, and challenges
behind real-time translation enhanced by contextual understanding.
Conclusion
With the help of computer linguistics, the effectiveness of language teaching can be
significantly increased. Interactive programs developed taking into account the peculiarities of
the Uzbek and English languages improve the quality of education, especially the effectiveness
of independent learning. NLP (Natural Language Processing) systems, which will be developed
in the future in the Uzbek language, will provide a wide range of opportunities not only for
foreigners, but also for our citizens who want to master the Uzbek language.
References:
1. Jurafsky, D., & Martin, J. H. (2021). Speech and Language Processing. Pearson.
2. Bozorov, B. (2018). O‘zbek tili grammatikasi va kompyuter lingvistikasi asoslari. Toshkent:
O‘zbekiston.
3. Manning, C. D., & Schütze, H. (1999). Foundations of Statistical Natural Language
Processing. MIT Press.
4. Абдураҳмонов, Ғ. (2020). Ҳисоблаш лингвистикаси ва ўзбек тили: истиқбол ва
муаммолар. – "Filologiya masalalari" jurnali.
