This paper describes the systems for the single-array track and the multiple-array track of the 5th CHiME Challenge. The final system is a combination of multiple systems, using Confusion Network Combination (CNC). The different systems presented here are utilizing different front-ends and training sets for a Bidirectional Long Short-Term Memory (BLSTM) Acoustic Model (AM). The front-end was replaced by enhancements provided by Paderborn University. The back-end has been implemented using RASR and RETURNN. Additionally, a system combination including the hypothesis word graphs from the system of the submission has been performed, which results in the final best system.