Method and apparatus for training semantic understanding model, electronic device, and storage medium

An electronic device, comprising:

• a memory, configured to store executable instructions;
• and
• a processor, configured to perform, when executing the executable instructions stored in the memory, a plurality of operations including:
• obtaining a first training sample set, the first training sample set comprising sentence samples with noise obtained through an active learning process;
• performing denoising processing on the first training sample set to form a corresponding second training sample set;
• processing the second training sample set by using a semantic understanding model, to determine initial parameters of the semantic understanding model;
• processing the second training sample set by using the semantic understanding model in response to the initial parameters of the semantic understanding model, to determine update parameters of the semantic understanding model;
• and
• iteratively updating a semantic representation layer network parameter and a task-related output layer network parameter of the semantic understanding model by using the second training sample set and according to the update parameters of the semantic understanding model.

A non-transitory computer-readable storage medium, storing executable instructions, the executable instructions, when executed by a processor of an electronic device, performing a plurality of operations including:

• obtaining a first training sample set, the first training sample set comprising sentence samples with noise obtained through an active learning process;
• performing denoising processing on the first training sample set to form a corresponding second training sample set;
• processing the second training sample set by using a semantic understanding model, to determine initial parameters of the semantic understanding model;
• processing the second training sample set by using the semantic understanding model in response to the initial parameters of the semantic understanding model, to determine update parameters of the semantic understanding model;
• and
• iteratively updating a semantic representation layer network parameter and a task-related output layer network parameter of the semantic understanding model by using the second training sample set and according to the update parameters of the semantic understanding model.