TEXT PREDICTION MODEL TRAINING METHOD AND APPARATUS

摘要

Disclosed are a text prediction model training method executed by a computer, and a text prediction model training apparatus. A text prediction model comprises a first prediction network (11) based on a time sequence, a buffer (12), and a second prediction network (13) based on the buffer (12). The training method comprises: inputting a t-th word in training text into a first prediction network (11), such that the first prediction network determines a first prediction probability for the next word according a state vector obtained by means of time sequence processing; in addition, reading, from a buffer (12), several fragment vectors formed on the basis of the previous text, and a second prediction network (13) obtaining a second prediction probability for the next word according to these fragment vectors; then, by taking an interpolation weight coefficient λ as a weighting coefficient of the second prediction probability, and taking one minus λ as a weighting coefficient of the first prediction probability, weighing and synthesizing the second prediction probability and the first prediction probability in order to obtain a comprehensive prediction probability; and at least according to the comprehensive prediction probability and a (t+1)th word, determining a prediction loss regarding the t-th word, and thereby training a text prediction model.