  Automated audio captioning is machine listening task whose goal is to
describe an audio using free text. An automated audio captioning system has to
be implemented as it accepts an audio as input and outputs as textual
description, that is, the caption of the signal. This task can be useful in
many applications such as automatic content description or machine-to-machine
interaction. In this work, an automatic audio captioning based on residual
learning on the encoder phase is proposed. The encoder phase is implemented via
different Residual Networks configurations. The decoder phase (create the
caption) is run using recurrent layers plus attention mechanism. The audio
representation chosen has been Gammatone. Results show that the framework
proposed in this work surpass the baseline system in challenge results.
