Résumé:
The main purpose of this project is to design an environmental
general audio content description using text, where a system accepts as an
input an audio signal and outputs the textual description of that signal.
This task has drawn lots of attention during the past several years
as a result of quick devolvement of different methods that can provide
captions for a general audio recording. To accomplish the automatic audio
captioning task, we have performed multiple experiments using a Clotho
dataset. Two deep neural networks have been employed in the
construction of our systems Recurrent Neural Network and Gated
Recurrent Unit, along with encoder-decoder architecture and a
combination of feature representations based on audio processing
techniques like Mel Spectrogram and text processing techniques used in
text decoding from word embeddings like one-hot-encoding and BERT.
Keywords: Audio Captioning, Machine Learning, Encoder Decoder Models, Signal Processing, Natural Language Processing.
