Empirical Analysis of Phrase-Based Statistical Machine Translation System for English to Hindi Language
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3AMJVR9XHH" target="_blank" >RIV/00216208:11320/22:MJVR9XHH - isvavai.cz</a>
Výsledek na webu
<a href="https://www.worldscientific.com/doi/10.1142/S219688882250004X" target="_blank" >https://www.worldscientific.com/doi/10.1142/S219688882250004X</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1142/S219688882250004X" target="_blank" >10.1142/S219688882250004X</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Empirical Analysis of Phrase-Based Statistical Machine Translation System for English to Hindi Language
Popis výsledku v původním jazyce
Hindi is the national language of India. However, most of the Government records, resolutions, news, etc. are documented in English which remote villagers may not understand. This fact motivates to develop an automatic language translation system from English to Hindi. Machine translation is the process of translating a text in one natural language into another natural language using computer system. Grammatical structure of Hindi language is very much complex than English language. The structural difference between English and Hindi language makes it difficult to achieve good quality translation results. In this paper, phrase-based statistical machine translation approach (PBSMT) is used for translation. Translation, reordering and language model are main working components of a PBSMT system. This paper evaluates the impact of various combinations of these PBSMT system parameters on automated English to Hindi language translation quality. Freely available n-gram-based BLEU metric and TER metric are used for evaluating the results.
Název v anglickém jazyce
Empirical Analysis of Phrase-Based Statistical Machine Translation System for English to Hindi Language
Popis výsledku anglicky
Hindi is the national language of India. However, most of the Government records, resolutions, news, etc. are documented in English which remote villagers may not understand. This fact motivates to develop an automatic language translation system from English to Hindi. Machine translation is the process of translating a text in one natural language into another natural language using computer system. Grammatical structure of Hindi language is very much complex than English language. The structural difference between English and Hindi language makes it difficult to achieve good quality translation results. In this paper, phrase-based statistical machine translation approach (PBSMT) is used for translation. Translation, reordering and language model are main working components of a PBSMT system. This paper evaluates the impact of various combinations of these PBSMT system parameters on automated English to Hindi language translation quality. Freely available n-gram-based BLEU metric and TER metric are used for evaluating the results.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
—
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Vietnam Journal of Computer Science
ISSN
2196-8888
e-ISSN
1469-8110
Svazek periodika
09
Číslo periodika v rámci svazku
02
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
28
Strana od-do
135-162
Kód UT WoS článku
000797588800002
EID výsledku v databázi Scopus
2-s2.0-85117257628