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Existing binaural approaches to speech segregation place an exclusive burden on cues related to the location of sound sources in space. These approaches can achieve excellent performance in anechoic conditions but degrade rapidly in realistic environments where room reverberation corrupts localization cues. In this paper, we propose to integrate monaural and binaural processing to achieve segregation and localization of voiced speech in reverberant environments. The proposed approach builds on monaural analysis for simultaneous organization, and combines it with a novel method for generation of location-based cues in a probabilistic framework that jointly achieves localization and sequential organization. We compare localization performance to two existing methods, sequential organization performance to a model-based system that uses only monaural cues, and segregation performance to an exclusively binaural system. Results suggest that the proposed framework allows for improved source localization and robust segregation of voiced speech in environments with considerable reverberation.