Hands-On Deep Learning Algorithms with Python

Language translation using the seq2seq model

The sequence-to-sequence model (seq2seq) is basically the many-to-many architecture of an RNN. It has been used for various applications because it can map an arbitrary-length input sequence to an arbitrary-length output sequence. Some of the applications of the seq2seq model include language translation, music generation, speech generation, and chatbots.

In most real-world scenarios, input and output sequences vary in length. For instance, let's take the language translation task, during which we need to convert a sentence from a source language to a target language. Let's assume we are converting from English (source) to French (target).

Consider our input sentence is what are you doing? Then, ...