homework for deep generation. Combine FastSpeech2 with different vocoders ⭐REFERENCE (modify origin repos): https://github.com/ming024/FastSpeech2 https://github.com/NVIDIA/waveglow https://github.com/mindslab-ai/univnet https://github.com/jik876/hifi-gan

TTS for Arabic (FastPitch) in the ONNX format

SA-toolkit: Speaker speech anonymization toolkit in python

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

zero-shot realtime TTS system, fully offline, free and open source

RADTTS + HiFiGAN vocoder

Speech synthesis (TTS) in low-resource languages by training from scratch with Fastpitch and fine-tuning with HifiGan

RepVgg + HiFiGAN

Ultrafast GAN based Vocoder for Text to Speech

Include Basis-MelGAN, MelGAN, HifiGAN and Multiband-HifiGAN, maybe NHV in the future.

This is an implementation for train hifigan part of XTTSv2 model using Coqui/TTS.

HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks

🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production