Distant-microphone automatic speech recognition (ASR) remains a challenging goal in everyday environments involving multiple background sources and reverberation. This paper reports on the results of the 2nd 'CHiME' Challenge, an initiative designed to analyse and evaluate the performance of ASR systems in a real-world domestic environment. We discuss the rationale for the challenge and provide a summary of the datasets, tasks and baseline systems. The paper overviews the systems that were entered for the two challenge tracks: small-vocabulary with moving talker and medium-vocabulary with stationary talker. We present a summary of the challenge findings including novel results produced by challenge system combination. Possible directions for future challenges are discussed.