HiFi-GAN

2000년 도입 · 논문 33편에서 사용

HiFi-GAN is a generative adversarial network for speech synthesis. HiFi-GAN consists of one generator and two discriminators: multi-scale and multi-period discriminators. The generator and discriminators are trained adversarially, along with two additional losses for improving training stability and model performance. The generator is a fully convolutional neural network. It uses a mel-spectrogram as input and upsamples it through transposed convolutions until the length of the output sequence matches the temporal resolution of raw waveforms. Every transposed convolution is followed by a multi-receptive field fusion (MRF) module. For the discriminator, a multi-period discriminator (MPD) is used consisting of several sub-discriminators each handling a portion of periodic signals of input audio. Additionally, to capture consecutive patterns and long-term dependencies, the multi-scale discriminator (MSD) proposed in MelGAN is used, which consecutively evaluates audio samples at different levels.

출처: HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis

소개 논문: HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis