Method and Apparatus For Training Speech Spectrum Generation Model, and Electronic Device

An electronic device, comprising:

• at least one processor;
• and
• a memory communicatively coupled to the at least one processor,
• wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform a method for training a speech spectrum generation model, the method comprising:
• inputting a first text sequence into the speech spectrum generation model to generate an analog spectrum sequence corresponding to the first text sequence, and to obtain a first loss value of the analog spectrum sequence according to a preset loss function;
• inputting the analog spectrum sequence corresponding to the first text sequence into an adversarial loss function model, which is a generative adversarial network model, to obtain a second loss value of the analog spectrum sequence;
• and
• training the speech spectrum generation model based on the first loss value and the second loss value.

A non-transitory computer-readable storage medium having computer instructions stored thereon, which are used to realize a method for training a speech spectrum generation model, the method comprising:

• inputting a first text sequence into the speech spectrum generation model to generate an analog spectrum sequence corresponding to the first text sequence, and to obtain a first loss value of the analog spectrum sequence according to a preset loss function;
• inputting the analog spectrum sequence corresponding to the first text sequence into an adversarial loss function model, which is a generative adversarial network model, to obtain a second loss value of the analog spectrum sequence;
• and
• training the speech spectrum generation model based on the first loss value and the second loss value.