Machine translation model for effective translation of Hindi poetries into English

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AZ7MGGD8Y" target="_blank" >RIV/00216208:11320/23:Z7MGGD8Y - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1080/0952813X.2020.1836033" target="_blank" >https://doi.org/10.1080/0952813X.2020.1836033</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/0952813X.2020.1836033" target="_blank" >10.1080/0952813X.2020.1836033</a>

Result language

angličtina

Original language name

Machine translation model for effective translation of Hindi poetries into English

Original language description

"The Word Sense Disambiguation (WSD) is a process of disambiguating the sense of the text according to its context. Machine translation is one of the challenging task since it requires effective representation of the text to capture semantic relation between Hindi lyrics in English normal language behaviour. This paper focuses on WSD methods to deal with dialects that convert Hindi lyrics to English in its syntactic structure of the words. WSD is a phenomenon for disambiguating the text so that machine would be capable to deduce correct sense of individual given words. WSD is critical for solving natural language tasks such as Machine Translation (MT) and speech processing. The distinguishing proof of significant words in Hindi as the language is not as simple as that of dialects in English. The interpretations of sonnets through the machines are exceptionally essential and deliberate about mind-blowing events. The interpretation of English ballads into other local dialects can turn out to be very straightforward, however, vice-versa is troublesome. This is due to the assortment of structures, classes, and feelings of the local dialects. Various endeavours have been connected far and wide towards the programmed interpretation of ballads from local dialects into English. In this paper, we propose a half breed MT (HBMT) procedure driven by the standard based MT together with measurements based on statistical machine translation (SMT) and rule-based machine translation (RBMT) for WSD in natural script Hindi in English Lyrics. This proposed method improves the semantic and syntactic accuracy of a machine interpretation framework. Finally, the proposed approach result is compared with the machine translation methods such a Google and Microsoft Bing Babylonian and HMT translators provided achieves a better outcome compared to the existing standards."

Czech name

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Czech description

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Type

J_ost - Miscellaneous article in a specialist periodical

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

"Journal of Experimental & Theoretical Artificial Intelligence"

ISSN

0952-813X

e-ISSN

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Volume of the periodical

34

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

15

Pages from-to

95-109

UT code for WoS article

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EID of the result in the Scopus database

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