Speech processing method and method for generating speech processing model

A method for generating a speech processing model, comprising:

• obtaining a training data set, wherein each group of data in the training data set comprises a reference signal, a speech signal carrying echo, and a labelled ideal ration mask (IRM);
• performing sub-band decomposition on the reference signal and the speech signal carrying echo in each group to obtain frequency-band components of the reference signal and the speech signal carrying echo in each group;
• processing the frequency-band components of the reference signal and the speech signal carrying echo in each group by using an initial neural network model, to obtain a predicted IRM corresponding to the reference signal in each group in each frequency-band component of the speech signal carrying echo;
• and
• performing back gradient propagation correction on the initial neural network model based on a difference between the predicted IRM of each group and the corresponding labelled IRM, to obtain a trained speech processing model;
• wherein processing the frequency-band components of the reference signal and the speech signal carrying echo in each group by using an initial neural network model, to obtain a predicted IRM corresponding to the reference signal in each group in each frequency-band component of the speech signal carrying echo comprises:
• performing multi-granularity feature extraction on each frequency-band component of the reference signal and the speech signal carrying echo in each group, to obtain features of each frequency-band component in each of the reference signal and the speech signal;
• and
• fusing the features of each frequency-band component in each of the reference signal and the speech signal, to obtain the predicted IRM corresponding to the reference signal in each group in each frequency-band component of the speech signal carrying echo.

An electronic device, comprising:

• at least one processor;
• and
• a memory communicatively coupled with the at least one processor;
• wherein, the memory stores instructions executable by the at least one processor that, when executed by the at least one processor, cause the at least one processor to perform a speech processing method, the method comprising:
• obtaining M speech signals to be processed and N reference signals, wherein M and N are positive integers equal to or greater than 1;
• performing sub-band decomposition on each of the M speech signals and each of the N reference signals to obtain frequency-band components in each speech signal and frequency-band components in each reference signal;
• processing the frequency-band components in each speech signal and the frequency-band components in each reference signal by using an echo cancellation model, to obtain an ideal ratio mask (IRM) corresponding to the N reference signals in each frequency band of each speech signal;
• and
• performing echo cancellation on each frequency-band component of each speech signal based on the ideal ratio mask corresponding to the N reference signals in each frequency band of each speech signal, to obtain M echo-cancelled speech signals;
• wherein processing the frequency-band components in each speech signal and the frequency-band components in each reference signal by using the echo cancellation model to obtain the IRM corresponding to the N reference signals in each frequency band of each speech signal comprises:
• performing multi-granularity feature extraction on each frequency-band component in the M speech signals and the N reference signals to obtain features of each frequency-band component in each of the M speech signals and the N reference signals;
• and
• fusing the features of each frequency-band components in each of the M speech signals and the N reference signals, to obtain the IRM corresponding to the N reference signals in each frequency band of each speech signal.