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

Effects of Layer Freezing on Transferring a Speech Recognition System to Under-resourced Languages