Provided is a training method for a character generation model. The training method for a character generation model includes: a first training sample is input into a target model to calculate a first loss, where the first training sample includes a first source domain sample word and a first target domain sample word, and content of the first source domain sample word is different from content of the first target domain sample word; a second training sample is input into the target model to calculate a second loss, where the second training sample includes a second source domain sample word and a second target domain sample word, content of the second source domain sample word is the same as content of the second target domain sample word; and a parameter of the character generation model is adjusted according to the first loss and the second loss.