  Audio captioning is a task that generates description of audio based on
content. Pre-trained models are widely used in audio captioning due to high
complexity. Unless a comprehensive system is re-trained, it is hard to
determine how well pre-trained models contribute to audio captioning system. To
prevent the time consuming and energy consuming process of retraining, it is
necessary to propose a preditor of performance for the pre-trained model in
audio captioning. In this paper, a series of pre-trained models are
investigated for the correlation between extracted audio features and the
performance of audio captioning. A couple of predictor is proposed based on the
experiment results.The result demonstrates that the kurtosis and skewness of
audio features extracted may act as an indicator of the performance of audio
captioning systems for pre-trained audio due to the high correlation between
kurtosis and skewness of audio features and the performance of audio captioning
systems.
