Language labeling method and computer device, and non-volatile storage medium

A language labeling computer device, comprising:

• at least one processor;
• a memory, configured to store at least one program;
• wherein the at least one processor, when loading and running the at least one program, is caused to perform:
• determining a language classifier;
• collecting a plurality of pieces of information correlated to video data, and determining the plurality of pieces of information as a plurality of pieces of video information;
• dividing the plurality of pieces of video information into target information and reference information;
• identifying languages to which the plurality of pieces of video information is attributed by inputting the plurality of pieces of video information into the language classifier;
• and
• checking a confidence level of a target language with an aid of reference languages, wherein the target language is a language to which the target information is attributed and the reference languages are a plurality of languages to which the reference information is attributed;
• in a case that the confidence level is greater than or equal to a preset confidence threshold, generating information similar to the video information to serve as incremental information;
• invoking the language classifier to detect a validity of the incremental information in identifying the target language;
• and
• in a case that the incremental information is valid for identifying the target language, updating the language classifier based on the target language and at least one of the video information or the incremental information.

A non-transitory computer-readable storage medium, storing one or more computer programs therein, wherein the one or more computer programs, when loaded and run by a processor, causes the processor to perform:

• determining a language classifier;
• collecting a plurality of pieces of information correlated to video data, and determining the plurality of pieces of information as a plurality of pieces of video information;
• dividing the plurality of pieces of video information into target information and reference information;
• identifying languages to which the plurality of pieces of video information is attributed by inputting the plurality of pieces of video information into the language classifier;
• and
• checking a confidence level of a target language with an aid of reference languages, wherein the target language is a language to which the target information is attributed and the reference languages are a plurality of languages to which the reference information is attributed;
• in a case that the confidence level is greater than or equal to a preset confidence threshold, generating information similar to the video information to serve as incremental information;
• invoking the language classifier to detect a validity of the incremental information in identifying the target language;
• and
• in a case that the incremental information is valid for identifying the target language, updating the language classifier based on the target language and at least one of the video information or the incremental information.