In this paper, a new concept of integrated hypothesis space for large vocabulary continuous speech recognition (LVCSR) system combination is proposed. Unlike the conventional systems combination approaches such as ROVER, the hypothesis spaces are directly integrated here without string alignment. In this way the timing information for all word hypotheses is well preserved and the new framework is more flexible on rescoring approaches used. Four rescoring criteria on the integrated hypothesis space were further explored and experiments on Chinese broadcast news corpus indicated improved performance.