An intelligent cross-language speech recognition and conversion method claimed by the present invention classifies speech data based on the language family, establishes inter-language distances, initially determines a language family to which to-be-recognized speech data belongs, and then performs language refined identification in the language family. After the first language identification error, neighbor language families can be further found based on established inter-language distances, and the language family is established; and after the language is identified, the language is convertedinto a standardized text, then the text is subjected to word segmentation, word frequency statistics and other processing to establish the mapping relationship, which facilitates subsequent voice query. On the one hand, the method effectively solves the disadvantages that the efficiency and the speed cannot be balanced in the current speech recognition. On the other hand, the processing of the speech text conversion is more reasonable, and the establishment of mapping relationship makes the recognition conversion efficiency more accurate.