  In this paper, we investigate the effect of layer freezing on the
effectiveness of model transfer in the area of automatic speech recognition. We
experiment with Mozilla's DeepSpeech architecture on German and Swiss German
speech datasets and compare the results of either training from scratch vs.
transferring a pre-trained model. We compare different layer freezing schemes
and find that even freezing only one layer already significantly improves
results.
