A sentence intent identification method, a device, and a computer readable storage medium, pertaining to the technical field of speech semantics. The method comprises: pre-processing original sentence samples, and obtaining pre-processed samples (S11); extracting sentence feature vectors from the pre-processed samples (S12); and training, on the basis of the sentence feature vectors, a sentence intent identification model by using a cross-entropy cost function method, and obtaining a trained sentence intent identification model (S13). The method further comprises: acquiring a target sentence to be identified (S14); outputting, on the basis of the target sentence, a sentence intent corresponding to the target sentence by using the trained sentence intent identification model (S15); and acquiring, from an answer database, an answer matching the sentence intent corresponding to the target sentence, and showing the answer to a user (S16). The method enables extraction of abstract features from speech data by using a deep neural network, and achieves accurate sentence identification.
SENTENCE INTENT IDENTIFICATION METHOD, DEVICE, AND COMPUTER READABLE STORAGE MEDIUM