In this paper

error-tolerant techniques are studied for large-vocabulary speaker-independent Chinese continuous speech recognition and understanding systems.When N-best syllable candidates with their corresponding acoustic scores are generated and a syllable lattice is constructed by the acoustic recognizer

an error-tolerant linguistic parser is used to search through the syllable lattice and find the optimal Chinese character sequence in which syllables of some characters may not be included in the lattice because additional possible candidates are considered.In such a way

some acoustic errors are corrected and the robustness of the parser is improved.Our experiments show that the error-tolerant parser can increase the understanding rate from 91.83%

a 28.4% error reduction over the conventional trigram model based parser without error-tolerant techniques.