MB-iSTFT-VITS2 and MB-iSTFT-VITS-with-AutoVocoder
These are ecosystem siblings where A represents the core MB-iSTFT-VITS2 implementation integrated into the standard vits2_pytorch framework, while B extends that same MB-iSTFT-VITS architecture with an additional AutoVocoder component as an alternative vocoding approach.
About MB-iSTFT-VITS2
FENRlR/MB-iSTFT-VITS2
Application of MB-iSTFT-VITS components to vits2_pytorch
This project helps you create custom text-to-speech (TTS) voices. You provide audio recordings and corresponding text transcripts, and it generates a model that can convert new text into natural-sounding speech in that voice. It's designed for speech synthesis researchers and engineers who want to build high-quality, potentially state-of-the-art TTS systems.
About MB-iSTFT-VITS-with-AutoVocoder
hcy71o/MB-iSTFT-VITS-with-AutoVocoder
Incorporating AutoVocoder to MB-iSTFT-VITS
This project helps create high-quality, natural-sounding synthetic speech from written text. It takes text as input and generates an audio file of someone speaking that text. This is designed for researchers and developers working on advanced text-to-speech (TTS) systems who want to improve the realism and speed of their voice synthesis models.
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