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We present an information fusion approach to robust recognition of microphone array speech for the recently launched 3rd CHiME Challenge. It is based on a deep learning framework with a large neural network consisting of subnets with different architectures. Multiple knowledge sources are integrated via an early fusion of normalized noisy features with different beamforming techniques, speech enhanced features, speaker related features, and other auxiliary features concatenated as the input todoi:10.1109/asru.2015.7404827 dblp:conf/asru/DuWTBDL15 fatcat:vjiezngqrrdqtnbzssymawsame