FCH-TTS
The FCH-TTS project enhances parallel speech synthesis by integrating advanced vocoder models such as MelGAN and incorporating SoftDTW for effective loss training. It is capable of achieving rapid synthesis on both CPU and GPU platforms. This project emphasizes voice style transfer, utilizing models that perform adeptly on datasets such as LJSpeech and LibriSpeech. The environment can be easily set up to synthesize high-quality speech, with comprehensive documentation and pretrained models available. An active community supports ongoing improvements, with detailed logging via TensorBoard and Wandb. Experience optimized configurations for efficient audio synthesis.
