Using a single acoustic model trained with 308 hrs of training data, which resulted after applying multi-array GSS data cleaning and a three-fold speed perturbation, we achieved a WER of 41.6 % on the development (DEV) and 43.2 % on the evaluation (EVAL) test set of CHiME-5, if the test data is also enhanced with multi-array GSS. This compares very favorably with the recently published topline in <cite>[13]</cite> , where the single-system best result, i.e., the WER without system combination, was 45.1 % and 47.3 % on DEV and EVAL, respectively, using an augmented training data set of 4500 hrs total.