This repository contains the implementation of a machine translation model using Encoder-Decoder architecture with Long Short-Term Memory (LSTM) cells. The model is designed to translate text from one ...

The notebook rnn_encoder_decoder.ipynb contains a detailed walkthrough of implementing this model in Keras, including: Data preprocessing for sequence-to-sequence models. Building the encoder and ...

The attention-based encoder-decoder (AED) speech recognition model has been widely successful in recent years. However, the joint optimization of acoustic model and language model in end-to-end manner ...

However, these approaches cannot be used directly for encoder-decoder model based end-to-end ASR, because the encoder-decoder model employs very different mechanisms from HMM-based approaches. In this ...

Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...

Our model adopts the encoder-decoder model. The encoder model improved the KBGAT model with a gate mechanism to control the attention mechanism and use entity embeddings to update relation embeddings.

In this article, we are going to see how we can remove noise from the image data using an encoder-decoder model. Having clear and processed images or videos is very important in any computer vision ...