A progressive reading method, comprising the following steps: training a first progressive reading model by using a first text sequence slice set to obtain a second progressive reading model (S20); using the second progressive reading model to sequentially predict slices in a second text sequence slice set to obtain prediction results, and calculating a cumulative prediction probability in which the prediction results are correct (S30); determining whether the cumulative prediction probability is less than a first preset threshold (S40); and if so, then stopping the prediction of the slices in the second text sequence slice set, and outputting the prediction results, and if not, then continuing to predict the slices in the second text sequence slice set until the cumulative prediction probability meets the preset threshold. The described method solves the technical problem of low answer recognition efficiency in reading scenarios.
PROGRESSIVE READING METHOD, APPARATUS AND DEVICE, AND READABLE STORAGE MEDIUM