Voice processing method and apparatus, electronic device, and computer-readable storage medium

A voice processing apparatus, comprising:

• a memory storing computer program instructions;
• and a processor coupled to the memory and configured to execute the computer program instructions and perform:
• determining a historical voice frame corresponding to a target voice frame;
• acquiring a frequency-domain characteristic of the historical voice frame and a time-domain parameter of the historical voice frame;
• obtaining a parameter set of the target voice frame according to a correlation between the frequency-domain characteristic of the historical voice frame and the time-domain parameter of the historical voice frame, the parameter set including at least two parameters;
• and
• reconstructing the target voice frame according to the parameter set,
• wherein the network model includes a first neural network and at least two second neural networks, the first neural network is in a cascade relationship with each of the second neural networks, and one of the second neural networks corresponding to a parameter in the parameter set, and obtaining the parameter set of the target voice frame comprises:
• invoking the first neural network based on the frequency-domain characteristic of the historical voice frame, to obtain a virtual frequency-domain characteristic of the target voice frame;
• and
• inputting the virtual frequency-domain characteristic of the target voice frame and the time-domain parameter of the historical voice frame to the at least two second neural networks respectively as input information, to obtain the at least two parameters in the parameter set of the target voice frame.

A non-transitory computer-readable storage medium storing computer program instructions executable by at least one processor to perform:

• determining a historical voice frame corresponding to a target voice frame;
• acquiring a frequency-domain characteristic of the historical voice frame and a time-domain parameter of the historical voice frame;
• obtaining a parameter set of the target voice frame according to a correlation between the frequency-domain characteristic of the historical voice frame and the time-domain parameter of the historical voice frame, the parameter set including at least two parameters;
• and
• reconstructing the target voice frame according to the parameter set,
• wherein the network model includes a first neural network and at least two second neural networks, the first neural network is in a cascade relationship with each of the second neural networks, and one of the second neural networks corresponding to a parameter in the parameter set, and obtaining the parameter set of the target voice frame comprises:
• invoking the first neural network based on the frequency-domain characteristic of the historical voice frame, to obtain a virtual frequency-domain characteristic of the target voice frame;
• and
• inputting the virtual frequency-domain characteristic of the target voice frame and the time-domain parameter of the historical voice frame to the at least two second neural networks respectively as input information, to obtain the at least two parameters in the parameter set of the target voice frame.