“Analysis and Implementation of the Translator Module in the Nagish App for Multilingual Communication”

Abstract— This paper analyzes the restatement module of the Nagish App, a multilingual communication tool designed to break down language walls in India. The app employs advanced neural machine restatement( NMT) ways to restate textbook and speech across several Indian languages. The paper discusses the system armature, data preprocessing, restatement models, and the technologies behind the module. The restatement system was estimated using multiple criteria , and the results demonstrate its eventuality for perfecting digital communication across verbal communities. This work contributes to developing real- time, accurate, and contextually applicable results for Indian languages. Keywords—Nagish App, Translation Module, Neural Machine Translation, Indian Languages, Text-to-Speech, Speech-to-Text.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-05-14
DOI
https://doi.org/10.55041/ijsrem47960
Primary Topic
Linguistic Education and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
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article

“Analysis and Implementation of the Translator Module in the Nagish App for Multilingual Communication”

Shajiya Dalwale
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Linguistic Education and Pedagogy
article

“Analysis and Implementation of the Translator Module in the Nagish App for Multilingual Communication”

Shajiya Dalwale
article en

Abstract

Abstract— This paper analyzes the restatement module of the Nagish App, a multilingual communication tool designed to break down language walls in India. The app employs advanced neural machine restatement( NMT) ways to restate textbook and speech across several Indian languages. The paper discusses the system armature, data preprocessing, restatement models, and the technologies behind the module. The restatement system was estimated using multiple criteria , and the results demonstrate its eventuality for perfecting digital communication across verbal communities. This work contributes to developing real- time, accurate, and contextually applicable results for Indian languages. Keywords—Nagish App, Translation Module, Neural Machine Translation, Indian Languages, Text-to-Speech, Speech-to-Text.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(05)
Solapur University (IN)
Openalex Percentile: Top 87%
Linguistic Education and Pedagogy
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