Methods and apparatuses for noise reduction based on time and frequency analysis using deep learning

A computer system for cancelling noise, the computer system comprising:

• a memory storing computer-readable instructions;
• and
• at least one processor configured to execute the computer-readable instructions to cause the computer systems to,
• generate a first voice signal by canceling a first portion of noise included in an input voice signal using a first network, the first network being a trained u-net structure, and the first portion of the noise being in a time domain,
• apply a first window to the first voice signal to obtain a first windowed voice signal,
• perform a fast Fourier transform (FFT) on the first windowed voice signal to acquire a magnitude signal and a phase signal,
• acquire a mask using a second network based on the magnitude signal, the second network being another trained u-net structure,
• apply the mask to the magnitude signal to obtain a masked magnitude signal,
• generate a second voice signal by canceling a second portion of the noise by performing an inverse fast Fourier transform (IFFT) on the first windowed voice signal based on the masked magnitude signal and the phase signal, and
• apply a second window to the second voice signal to obtain a second windowed voice signal.