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This paper considers the recognition of speech given in the form of two mixed sentences, spoken by the same talker or by two different talkers. The database published on the ICSLP2006 website for Two-Talker Speech Separation Challenge is used in the study. A system that recognizes and reconstructs both sentences from the given mixture is described. The system involves a combination of several different techniques, including a missing-feature approach for improving crosstalk/noise robustness, Wiener filtering for speech restoration, HMM-based speech reconstruction, and speakerdependent/- independent modeling for speaker/speech recognition. For clean speech recognition, the system obtained a word accuracy rate 96.7%. For the two-talker speech separation challenge task, the system obtained 81.4% at 6 dB TMR (target-to-masker ratio) and 34.1% at -9 dB TMR.