1. A voice recognition method, comprising: receiving, by a voice recognition device, an input voice, wherein the voice recognition device comprises a noise type detection engine, a storage area and a voice engine; acquiring, by the voice recognition device, a detection voice and a to-be-recognized voice by dividing the input voice, wherein a length of voice data comprised in the detection voice is less than a length of voice data comprised in the to-be-recognized voice; selecting, by the noise type detection engine after comparing the acquired detection voice with a voice training sample under a different sample environment, a sample environment corresponding to a voice training sample that has a minimum difference with the detection voice, as a detection environment type, wherein the sample environment comprises a quiet environment and a noise environment; detecting, by the voice recognition device, a storage area; outputting by the voice recognition device, when a recognizable previous environment type exists in the storage area, a voice correction instruction according to a result of comparison between the detection environment type and the previous environment type, wherein the previous environment type is a quiet environment or a noise environment; controlling, by the voice engine according to the voice correction instruction, correction on the to-be-recognized voice, and outputting an initial recognition result; separately comparing, by the noise type detection engine, the received to-be-recognized voice with a voice training sample under a different sample environment, and selecting a sample environment corresponding to a voice training sample that has a minimum difference with the to-be-recognized voice, as a current environment type; storing, by the voice recognition device, the current environment type to the storage area, and abandoning the current environment type after preset duration; and outputting, by the voice recognition device, a final recognition result after a confidence value of the initial recognition result is adjusted according to the current environment type.