A neural network-based text encoding method, an apparatus, a device, and a storage medium, relating to the field of neural networks. The method comprises: an encoder converts training text into a text sequence (101), and increases, according to left and right adjacent entropies of a target word, weights of associated words associated with the target word (103); an encoding modifier monitors, according to the weights of the associated words, a target associated word having the weight higher than a preset weight, and monitors the target word associated with the target associated word (104); update an encoding quality determining condition according to a first hidden state and a second hidden state of a decoder (105); if the encoding quality of an encoding result meets the encoding quality determining condition, the decoder decodes a target language sequence (107-1); and if not, adjusting vector representations of source sentences, repeatedly executing the operations above until the encoding quality meets the encoding quality determining condition, and then decoding the target language sequence (107-2). According to the method, vector representations of a source language sequence are continuously improved to be expressed to a target terminal, so that the effect of a translation model is improved.
NEURAL NETWORK-BASED TEXT ENCODING METHOD, APPARATUS, DEVICE, AND STORAGE MEDIUM