As the CEO of Bhashini, Nag is helping build the government's platform to make digital content and services more accessible across India's diverse languages ...

The Transformer architecture comprises two main modules: Encoder: Converts tokens into a three-dimensional vector space, capturing the text’s semantics and assigning importance to each token.

The original transformer architecture consists of two main components: an encoder and a decoder. The encoder processes the input sequence and generates a contextualized representation, which is then ...

This Project is based on multilingual Translation by using the Transformer with an encoder-decoder architecture along with the multi-head self-attention layers with the positional encoding and ...

CNNs excel in handling grid-like data such as images, RNNs are unparalleled in their ability to process sequential data, GANs offer remarkable capabilities in generating new data samples, Transformers ...

In machine learning, we have seen various kinds of neural networks and encoder-decoder models are also a type of neural network in which recurrent neural networks are used to make the prediction on ...

The encoder-decoder constructor framework for NMT proposed by Tu et al. (2017) adds a new ‘reconstructor’ structure to the original NMT model. It aims at doing translation from the hidden state of the ...