The present application relates to the field of artificial intelligence. Disclosed are a semantic understanding model training method and apparatus, a computer device, and a storage medium. The method comprises: obtaining a total word sequence corresponding to a training text from a training set; randomly selecting a preset number of continuous word vectors from the total word sequence, replacing the continuous word vectors with a mask sequence to obtain an input word sequence, and taking the preset number of continuous word vectors as a test output word sequence; inputting the input word sequence into an encoder-attention-decoder model for training to obtain a prediction output word sequence; according to a difference between the prediction output word sequence and the test output word sequence, adjusting model parameters of the encoder-attention-decoder model to reduce the difference; and returning to the step of inputting the input word sequence into an encoder-attention-decoder model for training to obtain a prediction output word sequence, continuing training, and stopping training until a preset training stop condition is satisfied, so as to obtain a semantic understanding model. The present application improves the understanding accuracy of a computer to the natural language.
SEMANTIC UNDERSTANDING MODEL TRAINING METHOD AND APPARATUS, COMPUTER DEVICE, AND STORAGE MEDIUM