Abstract: The autoregressive (AR) models, such as attention-based encoder-decoder models and RNN-Transducer, have achieved great success in speech recognition. They predict the output sequence ...

This tutorial is the sixth one from a series of tutorials that would help you build an abstractive text summarizer using tensorflow , today we would build an abstractive text summarizer in tensorflow ...

OpenNMT-tf is a general purpose sequence learning toolkit using TensorFlow 2. While neural machine translation is the main target task, it has been designed to more generally support: sequence to ...

Your browser does not support the audio element. This post tries to explain inner blocks of Transformer architecture which is the secret sauce behind all the Large ...

Back in the old days, traditional phrase-based translation systems performed their task by breaking up source sentences into multiple chunks and then translated them phrase-by-phrase. This led to ...

Abstract: In this article, a stochastic recurrent encoder decoder neural network (SREDNN), which considers latent random variables in its recurrent structures, is developed for the first time for the ...

Natural language processing (NLP) has undergone revolutionary changes in recent years. Thanks to the development and use of pre-trained language models, remarkable achievements have been made in many ...