Abstract: Provided are a model training method and apparatus, a machine translation method and apparatus, a device, and a storage medium. The model training method includes the steps described below. Through a neural network pruning technique, a respective influence degree of each parameter in multiple parameters in a first translation model on a translation result in a first field is determined to obtain at least one first parameter and at least one second parameter. By using the first corpus of the first field, the at least one first parameter is trained obtain the second translation model, and the at least one second parameter remains unchanged. Similarity between a translation result of the second translation model in the first field and a translation result of the first translation model in the first field meets a preset condition.

Abstract: Provided are a speech translation method, a device, and a storage medium. The method includes: extracting, through an encoder of an end-to-end speech translation model, the semantic feature of a to-be-processed speech; decoding, through a decoder of the end-to-end speech translation model, a source language text corresponding to the semantic feature from the semantic feature; decoding, through the decoder of the end-to-end speech translation model, the semantic feature according to the source language text to obtain a text sequence corresponding to the semantic feature; and splitting the text sequence to obtain a target language text corresponding to the to-be-processed speech.