Recurrent Neural Networks - RNNs are state-of-the-art models able to deliver very high accuracy in sequence modeling and machine translation tasks. In particu- lar the Encoder-Decoder architecture excels in sequence-to-sequence tasks in which input and output sequences may not have the same length. These networks work in two stages, at first the input sequence is encoded in a fixed length representa- tion, which is then decoded in order to produce a new target sequence. Due to the abundance of the network parameters, performing inference using these models requires a high computing power and results in large energy consumption, typically unsustainable for an embedded device.