  We introduce a dictionary containing forms of common words in various Swiss
German dialects normalized into High German. As Swiss German is, for now, a
predominantly spoken language, there is a significant variation in the written
forms, even between speakers of the same dialect. To alleviate the uncertainty
associated with this diversity, we complement the pairs of Swiss German - High
German words with the Swiss German phonetic transcriptions (SAMPA). This
dictionary becomes thus the first resource to combine large-scale spontaneous
translation with phonetic transcriptions. Moreover, we control for the regional
distribution and insure the equal representation of the major Swiss dialects.
The coupling of the phonetic and written Swiss German forms is powerful. We
show that they are sufficient to train a Transformer-based phoneme to grapheme
model that generates credible novel Swiss German writings. In addition, we show
that the inverse mapping - from graphemes to phonemes - can be modeled with a
transformer trained with the novel dictionary. This generation of
pronunciations for previously unknown words is key in training extensible
automated speech recognition (ASR) systems, which are key beneficiaries of this
dictionary.
