To reduce background noise in quiet sections of an audio synthesis GAN, apply spectral denoising techniques like Wiener filtering, train with perceptual loss, or use a post-processing denoiser such as Wave-U-Net.
Here is the code snippet you can refer to:

In the above, we are using the following key points:
- Audio Loading: Reads the generated audio file and converts it to mono if needed.
- STFT Calculation: Computes the Short-Time Fourier Transform (STFT) for frequency analysis.
- Wiener Filtering: Applies Wiener filtering to reduce background noise in quiet sections.
- ISTFT Reconstruction: Converts the denoised spectrogram back into an audio signal.
- Spectrogram Visualization: Displays before-and-after spectrograms to analyze noise reduction effectiveness.
Hence, by applying Wiener filtering to the spectrogram, we effectively reduce background noise in quiet sections of the synthesized audio, enhancing the quality of the generated sound.