This repository contains an implementation of the Transformer Encoder-Decoder model from scratch in C++. The objective is to build a sequence-to-sequence model that leverages pre-trained word ...

This project aims to create a chatbot using the Transformer encoder-decoder model, based on the groundbreaking "Attention Is All You Need" paper. The Transformer architecture has revolutionized ...

Within a multi-task learning framework, we introduce two pre-training tasks for the encoder-decoder network using acoustic units, i.e., pseudo codes, derived from an offline clustering model. One is ...

This is particularly true for the simplest form of a single block encoder-decoder Transformer model, which can be finely tuned through optimised hyperparameters. This paper examines the performance of ...

Abstract: We present competitive results using a Transformer encoder-decoder-attention model for end-to-end speech recognition needing less training time compared to a similarly performing LSTM model.

Researchers from Google AI, NVIDIA, Ludwig-Maximilians-University, and Technical University of Munich (TUM) have recently published a paper describing CodeTrans, an encoder-decoder transformer model ...