SpecGAN

2000년 도입 · 논문 1편에서 사용

SpecGAN is a generative adversarial network method for spectrogram-based, frequency-domain audio generation. The problem is suited for GANs designed for image generation. The model can be approximately inverted. To process audio into suitable spectrograms, the authors perform the short-time Fourier transform with 16 ms windows and 8ms stride, resulting in 128 frequency bins, linearly spaced from 0 to 8 kHz. They take the magnitude of the resultant spectra and scale amplitude values logarithmically to better-align with human perception. They then normalize each frequency bin to have zero mean and unit variance. They clip the spectra to $3$ standard deviations and rescale to $\left[−1, 1\right]$. They then use the DCGAN approach on the result spectra.

출처: Adversarial Audio Synthesis

소개 논문: Adversarial Audio Synthesis