Authors :
K. Nehasri; P. Uma Sankar; P. Suresh; P. P. N. S. Gowthami; B. Umesh Krishna
Volume/Issue :
Volume 8 - 2023, Issue 11 - November
Google Scholar :
https://tinyurl.com/4m3h2y85
Scribd :
https://tinyurl.com/3ryna99b
DOI :
https://doi.org/10.5281/zenodo.10300081
Abstract :
Interactive language translators are like magic
biases that use smart technology to help you communicate
with others who speak a different language they come in
colorful formsfrom apps on your phone to devoted bias and
they are making communication easier for trippers
businesses and associations that operate on a global scale
but these translators do further than just change words
from one language to another they also capture the
meaning behind the words and the passions people are
trying to express its nearly like having a particular
language adjunct that ensures you are not just
understanding the words but also the environment and
feelings LSTM a type of intermittent neural network is
employed in this translator to address the complications
of natural language processing unlike traditional machine
restatement systems which frequently produce stiff and
awkward restatements LSTM algorithms are designed to
capture contextual and grammatical nuances enabling a
more fluent and mortal- suchlike affair this composition
provides an overview of the LSTM algorithm and its
applicability to language restatement we explore how
LSTM models can learn sequences and patterns in
languages making them well-suited for tasks like
restatement also we claw into theinteractive nature of this
translator which enables druggies to engage in flawless
exchanges with speakers of other languages the proposed
interactive language translator represents a significant
advancement in the field of machine restatement offering
a stoner-friendly real- time result for prostrating
language walls it promises to grease cross-cultural
communication foster global cooperation and open doors
to new openings in a decreasingly connected world.
Keywords :
LSTM, NMT, Speech Recognition, Speech-To- Speech, Attention Mechanism, Encoder-Decoder, Language Translation.
Interactive language translators are like magic
biases that use smart technology to help you communicate
with others who speak a different language they come in
colorful formsfrom apps on your phone to devoted bias and
they are making communication easier for trippers
businesses and associations that operate on a global scale
but these translators do further than just change words
from one language to another they also capture the
meaning behind the words and the passions people are
trying to express its nearly like having a particular
language adjunct that ensures you are not just
understanding the words but also the environment and
feelings LSTM a type of intermittent neural network is
employed in this translator to address the complications
of natural language processing unlike traditional machine
restatement systems which frequently produce stiff and
awkward restatements LSTM algorithms are designed to
capture contextual and grammatical nuances enabling a
more fluent and mortal- suchlike affair this composition
provides an overview of the LSTM algorithm and its
applicability to language restatement we explore how
LSTM models can learn sequences and patterns in
languages making them well-suited for tasks like
restatement also we claw into theinteractive nature of this
translator which enables druggies to engage in flawless
exchanges with speakers of other languages the proposed
interactive language translator represents a significant
advancement in the field of machine restatement offering
a stoner-friendly real- time result for prostrating
language walls it promises to grease cross-cultural
communication foster global cooperation and open doors
to new openings in a decreasingly connected world.
Keywords :
LSTM, NMT, Speech Recognition, Speech-To- Speech, Attention Mechanism, Encoder-Decoder, Language Translation.
