I have a manuscript which has been reviewed and one of the reviewer commented on my use of the term **"data augmentation"**, saying that it might not be the appropriate term in my case (explained below).

I collected a large dataset of short audio files which are used to train a Convolutional Neural Network. Before being used as model input, each audio file is processed through a pipeline that mixes it with other audio files, changes some of the sound properties (SNR ratio, distorting the audio ...) and finally convert it in a mel-spectrogram. I only modify the existing file and I do not increase my training dataset but I refer this processing as "**data augmentation**".

I did not find any definitive definition of what is data augmentation. For instance, [Salamon and Bello, 2016][1] define data augmentation as 

> the application of one or more deformations to a collection of
> annotated training samples which result in new, additional training
> data

However, it appears to me that the increase in the training dataset is only a byproduct of the data augmentation.

In any case I would really appreciate if you could confirm or not my use of "data augmentation" and I would be grateful if you can provide a reference for this.


  [1]: https://arxiv.org/abs/1608.04363