With the rapid advancement of natural language processing (NLP), machine translation (MT) has evolved from rule-based methods to neural machine translation (NMT).Our project explores Transformer-based ...

The Encoder and Decoder would also have the embedding layer and hold the positional encodings as well that get added to the embeddings. These are then passed on to the Encoding/Decoding layers.

Since being open sourced by Google in November 2018, BERT has had a big impact in natural language processing (NLP) and has been studied as a potentially promising way to further improve neural ...

The recently proposed BERT has shown great power on a variety of natural language understanding tasks, such as text classification, reading comprehension, etc. However, how to effectively apply BERT ...

Smooth language translation is becoming more and more important in today's globalized society as it promotes efficient communication, knowledge sharing, and intercultural understanding. The study ...

We explore the application of very deep Transformer models for Neural Machine Translation (NMT). Using a simple yet effective initialization technique that stabilizes training, we show that it is ...