Deep Learning Based Method and System for Processing Sound Quality Characteristics

A method comprising:

• extracting preference data of a user;
• determining data characteristics of the preference data;
• generating a personalized sound quality characteristic processing model by:
• outputting sound quality characteristics processing results based on a baseline model, and
• updating the baseline model based on feedback data from the user on the sound quality characteristics processing results,
• based on a determining that a number of individual user feedback behaviors in user behavior data exceeds a predetermined value, relearning the baseline model or the personalized sound quality characteristics processing model based on the preference data of the user;
• and
• generating a personalized sound quality characteristic processing result based on the personalized sound quality characteristic processing model.

A method comprising:

• determining, based on extracted features from audio data associated with a user, data characteristics of the audio data;
• based on a determination that the data characteristics are associated with noise, training a neural network model by:
• extracting data features and corresponding category tag features from audio data associated with a plurality of users, wherein the audio data associated with the plurality of users comprises noise or normal sound category tag features;
• and
• training the neural network model based on the data features and the corresponding category tag features;
• and
• based on the data characteristics and the neural network model, generating a sound quality processing result of the audio data associated with the user.