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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM12150

A Preliminary Work on Speech to Speech Translation

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM12150

Volume:

6 |

4 |

Apr 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM12150

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PP

Priyanka Padmane

AP

Ayush Pakhale

SA

Sagar Agrel

AP

Ankita Patel

SP

Sarvesh Pimparkar

PB

Prajwal Bagde

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Abstract

The automatic translation with one human language into another is referred to as “machine translation.” The main purpose is to bridge the linguistic gap between people who speak different languages, communities, or countries. There are 18 main language and ten scripts that are frequently used. Because the majority of Indians, particularly remote peasants, cannot understand, read, or write English, an excellent language translator is required. Machine translation systems that transform source text to another will assist Indians in living in a more enlightened society without language barriers. Because English is a worldwide language and Hindi is the language spoken by the majority of Indians, we propose an English to Hindi machine translation system based on recurrent neural networks (RNN), LSTM (Long short-term memory), and attention processes. The automatic translation of one natural language into another is referred to as “machine translation.” The main purpose is to bridge the linguistic gap between people who speak different languages, communities, or countries. There are 18 official languages and ten scripts that are frequently used. The majority of Indians, particularly isolated peasants, do not understand, read, or write English, necessitating the implementation of an effective language translator. Machine translation systems that convert text from one language to another will help Indians live in a more enlightened society that is free of language barriers.

KEYWORDS

RNN LSTM Speech to text text to Speech Multi linguistic.

Cite This Article

Priyanka Padmane, Ayush Pakhale, Sagar Agrel, Ankita Patel, Sarvesh Pimparkar, Prajwal Bagde, "A Preliminary Work on Speech to Speech Translation," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 4, Apr 2022. https://doi.org/10.55041/IJSREM12150

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Publication Date

4/3/2022

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Double-Blind Peer Review

Review Rounds: 2

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