to download of transliteration

We provide transliteration project in this paper. Transliteration is the process of mapping text written in one language into
another by means of a pre-defined mapping. It is useful when a user knows a language
but does not know how to write its script. Hindi is the lingua-franca of India. It is the
most widely spoken and scripted language in India. Transliteration helps people
pronounce words and names in foreign languages. Transliteration aims to only change
the letters or characters of a source language into corresponding letters of the target
language. It does not render meaning unlike translation, which is converts the written or
spoken meanings of words or text of a source language into a target language.
Given a word in English, the model represents the same word in Devanagari
script (Hindi) using two Recurrent neural networks i.e. an Encoder and a Decoder.
The encoder network is that part of the network that takes the input sequence in English
and maps it to an encoded representation of the sequence. The encoded representation
is then used by the decoder network to generate an output sequence in Hindi.
Transliteration can used effectively in the case of nouns. The accuracy of the model can
be further increased with attention mechanism used in combination with Encoder Decoder Model

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. “A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.” This is Alan Turing’s
definition of machine learning.Deep learning is a class of machine learning algorithms that utilizes a
hierarchical level of artificial neural networks to carry out the process of machine learning. The artificial neural networks are built like the human brain, with neuron nodes connected together like a web. While traditional programs build analysis with data in a linear way, the hierarchical function of deep learning systems enables machines to process data with a nonlinear approach. The word “deep” in “deep learning” refers to the number of layers through which the data is transformed. More precisely, deep learning systems have a substantial credit assignment path (CAP) depth. The CAP is the chain of transformations from input to output.CAPs describe potentially causal connections between input and output.For a feedforward neural network, the depth of the CAPs is that of the network and is the number of hidden layers plus one (as the output layer is also parameterized).For recurrent neural networks, in which a signal may propagate through a layer more than once, the CAP depth is potentially unlimited.
Natural language processing (NLP) is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyse large amounts of natural language data .Deep learning architectures such as deep neural networks, deep belief networks,
recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, speech recognition, natural language processing,audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases superior to human experts.

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