The invention discloses a multi-modal neural machine translation method. The method comprises the following steps: constructing a multi-modal neural machine translation model comprising a visual entity detector, an encoder and a decoder; the encoder comprises a bidirectional GRU module and a visual entity and source language attention module which are connected in sequence; the decoder comprises a multi-head attention layer and a one-way GRU module which are connected in sequence; the visual entity detector is used for identifying and extracting a visual entity feature vector in the image, and respectively outputting the extracted visual entity feature vector to the bidirectional GRU module and the visual entity and source language attention module; and aggregating the outputs of the bidirectional GRU module and the visual entity and source language attention module into a mixed-mode source language feature vector by using a sequence feature average pooling method, and inputting the aggregated source language feature vector into a decoder. The invention further discloses a computer device and a storage medium which are cooperatively implemented. According to the method, the fine-grained matching effect and translation effect between the visual entity and the text are improved.
Multi-modal neural machine translation method, computer equipment and storage medium