  The field of audio captioning has seen significant advancements in recent
years, driven by the availability of large-scale audio datasets and
advancements in deep learning techniques. In this technical report, we present
our approach to audio captioning, focusing on the use of a pretrained
speech-to-text Whisper model and pretraining on synthetic captions. We discuss
our training procedures and present our experiments' results, which include
model size variations, dataset mixtures, and other hyperparameters. Our
findings demonstrate the impact of different training strategies on the
performance of the audio captioning model. Our code and trained models are
publicly available on GitHub and Hugging Face Hub.
