This repository implements the the encoder and decoder model with attention model for OCR, the encoder uses CNN+Bi-LSTM, the decoder uses GRU.

We study a streamable attention-based encoder-decoder model in which either the decoder, or both the encoder and decoder, operate on pre-defined, fixed-size windows called chunks. A special ...

End-to-end (E2E) models, including the attention-based encoder-decoder (AED) models, have achieved promising performance on the automatic speech recognition (ASR) task. However, the supervised ...

To generate each part of translation, the attention mechanism tells a Neural Machine Translation model where it should pay attention to. A simple encoder-decoder model without the attention mechanism ...

Many computational methods have been proposed to predict drug–drug interactions (DDIs), which can occur when combining drugs to treat various diseases, but most mainly utilize single-source features ...

Tech giant Microsoft (MSFT) has launched a new small language model called Mu that is built to handle complex language tasks efficiently on devices like Copilot+ PCs. Unlike larger AI models that run ...

The encoder’s self-attention mechanism helps the model weigh the importance of each word in a sentence when understanding its meaning. Pretend the transformer model is a monster: ...