  The CHiME challenge series aims to advance robust automatic speech
recognition (ASR) technology by promoting research at the interface of speech
and language processing, signal processing , and machine learning. This paper
introduces the 5th CHiME Challenge, which considers the task of distant
multi-microphone conversational ASR in real home environments. Speech material
was elicited using a dinner party scenario with efforts taken to capture data
that is representative of natural conversational speech and recorded by 6
Kinect microphone arrays and 4 binaural microphone pairs. The challenge
features a single-array track and a multiple-array track and, for each track,
distinct rankings will be produced for systems focusing on robustness with
respect to distant-microphone capture vs. systems attempting to address all
aspects of the task including conversational language modeling. We discuss the
rationale for the challenge and provide a detailed description of the data
collection procedure, the task, and the baseline systems for array
synchronization, speech enhancement, and conventional and end-to-end ASR.
