Augmented attribute grammar in meaning of natural languages sentences

Tukeyev, Ualsher; Rakhimova, Diana

doi:10.1109/scis-isis.2012.6505191

Cited by 3 publications

(2 citation statements)

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“…Through the work of the research group under Professor U. A. Tukeyev's guidance, grammatical formal models of simple sentences and the first version of a machine translation program (MTP) from Kazakh to English were defined [13,14]. Additionally, a polysemous method for machine translation of morphologically complex natural languages such as Russian and Kazakh was developed [15][16][17].…”

Section: Review Of Research Studiesmentioning

confidence: 99%

The Task of Post-Editing Machine Translation for the Low-Resource Language

Rakhimova,

Karibayeva,

Turarbek

2024

Applied Sciences

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In recent years, machine translation has made significant advancements; however, its effectiveness can vary widely depending on the language pair. Languages with limited resources, such as Kazakh, Uzbek, Kalmyk, Tatar, and others, often encounter challenges in achieving high-quality machine translations. Kazakh is an agglutinative language with complex morphology, making it a low-resource language. This article addresses the task of post-editing machine translation for the Kazakh language. The research begins by discussing the history and evolution of machine translation and how it has developed to meet the unique needs of languages with limited resources. The research resulted in the development of a machine translation post-editing system. The system utilizes modern machine learning methods, starting with neural machine translation using the BRNN model in the initial post-editing stage. Subsequently, the transformer model is applied to further edit the text. Complex structural and grammatical forms are processed, and abbreviations are replaced. Practical experiments were conducted on various texts: news publications, legislative documents, IT sphere, etc. This article serves as a valuable resource for researchers and practitioners in the field of machine translation, shedding light on effective post-editing strategies to enhance translation quality, particularly in scenarios involving languages with limited resources such as Kazakh and Uzbek. The obtained results were tested and evaluated using specialized metrics—BLEU, TER, and WER.

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Section: Review Of Research Studiesmentioning

confidence: 99%

The Task of Post-Editing Machine Translation for the Low-Resource Language

Rakhimova,

Karibayeva,

Turarbek

2024

Applied Sciences

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“…On the basis of context-free grammar, the formalization of the semantics of the language is provided by the attribute grammar. In the proposed methodology, demonstration of semantic analysis of text of natural language is applied with the help of attribute grammar [3].…”

Section: Introductionmentioning

confidence: 99%

Sentence Formation in NLP Engine on the Basis of Indian Sign Language using Hand Gestures

Agarwal¹,

Agrawal²,

Latif³

2015

IJCA

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A person who is hearing impaired or mute is not able to compete or work with a normal person because of lack of proper communication between the two. This paper presents the development of an application which will enable a hassle free communication between physically disabled person and normal person. The application is responsible for the conversion of hand gestures into a meaningful sentence which can be read out by a normal person. In this approach, gestures based on Indian sign language are used. The major steps associated with the application are gesture recognition and natural language processing as most important module in the paper proposed. The current work can be used as an interface to communicate with speech impaired and normal person. Thus, it will bridge the gap between speech impaired and normal people by capturing sign processing it recognizing it & presenting output as meaningful sentence.

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