  In this work, we studied the synthesis of Swiss German speech using different
Text-to-Speech (TTS) models. We evaluated the TTS models on three corpora, and
we found, that VITS models performed best, hence, using them for further
testing. We also introduce a new method to evaluate TTS models by letting the
discriminator of a trained vocoder GAN model predict whether a given waveform
is human or synthesized. In summary, our best model delivers speech synthesis
for different Swiss German dialects with previously unachieved quality.
