Voice information processing method and apparatus, and terminal

A terminal, comprising:

• a processor;
• and
• a memory coupled to the processor and storing instructions that, when executed by the processor, cause the terminal to be configured to:
• receive voice information;
• perform semantic understanding on the voice information to convert the voice information into text information;
• obtain a field probability that the text information belongs to each of M event fields, wherein the M event fields are preset in the terminal, wherein the field probability represents a possibility that the text information belongs to one of the M event fields;
• obtain a prior probability that the text information belongs to each of N event fields, wherein the prior probability represents a probability that the text information belongs to one of the M event fields based on a plurality of times the terminal performs the semantic understanding, wherein the N event fields are N of the M event fields, and wherein N is less than or equal to M;
• obtain confidence that the text information belongs to each of the N event fields, wherein the confidence represents a certainty degree that the text information belongs to one of the N event fields;
• calculate the prior probability and the confidence that the text information belongs to each of the N event fields based on the field probability, wherein values of N probabilities correspond to whether the text information belongs to the N event fields;
• and
• output a semantic understanding result in response to performing the semantic understanding on the text information based on an event field of a largest probability value in the values of N probabilities.

A computer program product comprising computer-executable instructions for storage on a non-transitory computer-readable medium that, when executed by a processor, cause a terminal to:

• receive voice information;
• perform semantic understanding on the voice information to convert the voice information into text information;
• obtain a field probability that the text information belongs to each of M event fields, wherein the M event fields are preset in the terminal, and wherein the field probability represents a possibility that the text information belongs to one of the M event fields;
• obtain a prior probability that the text information belongs to each of N event fields, wherein the prior probability represents a probability that the text information belongs to one of the N event fields based on a plurality of times of performing the semantic understanding, wherein the N event fields are N of the M event fields, and wherein N is less than or equal to M;
• obtain confidence that the text information belongs to each of the N event fields, wherein the confidence represents a certainty degree that the text information belongs to one of the N event fields;
• calculate, based on the field probability, the prior probability, and the confidence that the text information belongs to each of the N event fields, wherein values of N probabilities correspond to whether the text information belongs to the N event fields;
• and
• output a semantic understanding result in response to performing the semantic understanding on the text information based on an event field of a largest probability value in the values of N probabilities.