The invention relates to the technical field of language
data processing, and discloses a language data preprocessing method in a multilingual and complex scene, which is a
voice data preprocessing
system in the multilingual and complex scene based on an AutoPrep framework, integrates five modules, namely a voice enhancement module, a voice segmentation module, a speaker clustering module, a target voice extraction module and a quality filtering module. According to the scheme, differential suppression of steady-state
noise and transient-state
noise in multilingual voice signals is realized, and particularly in a small language (such as Kazakh and Talanx) scene, the voice
signal-to-
noise ratio and the
language independence of voice features are effectively improved, so that the
voice data can be automatically and structurally processed, and the voice
signal-to-noise ratio and the
language independence of the voice features can be effectively improved. The problem that in the prior art, the phoneme mapping error rate is high due to the fact that small languages lack an exclusive phoneme
system processing module is solved, and the availability and the
processing effect of low-resource language data are enhanced.