The embodiment of the invention provides a Chinese
spoken language semantic comprehension method. The method comprises the steps of obtaining a generalized
label-free text sequence
training set, and performing forward prediction and reverse prediction on the
training set in sequence to
train a word-level and a word-level bidirectional
language model; receiving
spoken language voice audios input bya user, and carrying out sequence word segmentation to obtain character sequences and word sequences; decoding the character sequence and the word sequence by using the character-level bidirectionallanguage model and the word-level bidirectional
language model respectively to obtain character-level implicit strata vectors and word-level implicit strata vectors; performing vector alignment on theimplicit strata vectors of the character sequence and the word sequence to obtain an implicit strata vector of
spoken language voice audio input by the semantic comprehension model; and inputting thehidden layer vector of the spoken language voice audio into a semantic comprehension model, and determining the
semantics of the spoken language voice audio. The embodiment of the invention further provides a Chinese spoken language semantic comprehension
system. The embodiment of the invention has good generalization ability, combines word and character sequences, and improves the performance ofChinese semantic comprehension.