  This paper describes the winning approach in the Shared Task 3 at SwissText
2021 on Swiss German Speech to Standard German Text, a public competition on
dialect recognition and translation. Swiss German refers to the multitude of
Alemannic dialects spoken in the German-speaking parts of Switzerland. Swiss
German differs significantly from standard German in pronunciation, word
inventory and grammar. It is mostly incomprehensible to native German speakers.
Moreover, it lacks a standardized written script. To solve the challenging
task, we propose a hybrid automatic speech recognition system with a lexicon
that incorporates translations, a 1st pass language model that deals with Swiss
German particularities, a transfer-learned acoustic model and a strong neural
language model for 2nd pass rescoring. Our submission reaches 46.04% BLEU on a
blind conversational test set and outperforms the second best competitor by a
12% relative margin.
