The Luong attention sought to introduce several improvements over the Bahdanau model for neural machine translation, notably by introducing two new classes of attentional mechanisms: a global approach that attends to all source words and a local approach that only attends to a selected subset of words in predicting the target sentence. In this tutorial, […]
Conventional encoder-decoder architectures for machine translation encoded every source sentence into a fixed-length vector, regardless of its length, from which the decoder would then generate a translation. This made it difficult for the neural network to cope with long sentences, essentially resulting in a performance bottleneck. The Bahdanau attention was proposed to address the performance […]
