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 ...

Resources about word vectors, aka word embeddings, and distributed representations for words. Word vectors are numeric representations of words where similar words have similar vectors. Word vectors ...

This post tries to explain inner blocks of Transformer architecture which is the secret sauce behind all the Large language models and Chatbots with an example. Historically RNN’s like LSTM’s and ...

Deep learning architectures have revolutionized the field of artificial intelligence, offering innovative solutions for complex problems across various domains, including computer vision, natural ...

In this paper, a novel fusion network for automatic modulation classification (AMC) is proposed in underwater acoustic communication, which consists of a Transformer and depth-wise convolution (DWC) ...

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 ...