Abstract：An improved lattice-based speech keyword spotting system was developed from the Gaussian mixture model and an improved N-best speech recognition algorithm. First, tests were used to evaluate different simplified structures of Gaussian mixture models. Then, an N-best token passing algorithm was developed from the classic token passing algorithm using some unique pronunciation rules for the Chinese language. These two modifications improve the performance of both the 1-best and N-best speech recognition candidates. Finally, a key word spotting system was developed based on an N-best lattice to show the effectiveness of these improvements.