Training method and enhancement method for speech enhancement model, apparatus, electronic device, storage medium and program product

A training apparatus for a speech enhancement model, the apparatus comprising:

• an enhancement module, configured to invoke a speech enhancement model based on a noisy speech feature of a noisy speech signal, to perform speech enhancement, to obtain a plurality of first predicted mask values in an auditory domain, the plurality of first predicted mask values having a one-to-one correspondence with a plurality of frequency bands in the auditory domain;
• an obtaining module, configured to obtain a first amplitude and a first phase corresponding to each frequency point of the noisy speech signal, and a second amplitude and a second phase corresponding to each frequency point of a clean speech signal;
• a correction module, configured to determine a phase difference between the clean speech signal and the noisy speech signal at each frequency point based on the first phase and the second phase corresponding to each frequency point, and correct the second amplitude corresponding to the frequency point based on the phase difference at each frequency point, to obtain a corrected second amplitude corresponding to each frequency point;
• a determining module, configured to determine a loss value based on the plurality of first predicted mask values, and the first amplitude and the corrected second amplitude corresponding to each frequency point;
• and
• an update module, configured to perform backpropagation in the speech enhancement model based on the loss value to update parameters of the speech enhancement model.

A non-transitory computer-readable storage medium, having executable instructions stored therein, the executable instructions, when executed by a processor, causing an apparatus to perform:

• invoking a speech enhancement model based on a noisy speech feature of a noisy speech signal, to perform speech enhancement on the noisy speech signal, to obtain a plurality of first predicted mask values, the plurality of first predicted mask values having a one-to-one correspondence with a plurality of frequency bands in an auditory domain;
• obtaining a first amplitude and a first phase corresponding to each frequency point of the noisy speech signal, and a second amplitude and a second phase corresponding to each frequency point of a clean speech signal;
• determining a phase difference between the clean speech signal and the noisy speech signal at each frequency point based on the first phase and the second phase corresponding to each frequency point;
• correcting the second amplitude corresponding to the frequency point based on the phase difference, to obtain a corrected second amplitude corresponding to each frequency point;
• determining a loss value based on the plurality of first predicted mask values, and the first amplitude and the corrected second amplitude corresponding to each frequency point;
• and
• performing backpropagation in the speech enhancement model based on the loss value, to update parameters of the speech enhancement model.