Hey I’m planning to do an experiment with DeepSpeech version v0.8.2, using three different magnitudes of add augmentation in the training. Then comparing the three models for three test sets containing again three different amounts of noise.
As I am using google collab I have limited disk space and I can’t use the 50gb common voice dataset for training.
My question is - Can I somehow split that dataset so I’m only using for example 10 gb of the data in it? .
Also the testing of the models should be done with inference or as the test_files while training ?
Furthermore, for testing the models, do I search for datasets which already have noise in it or should i create that from a clean dataset.
Thanks in advance!