92 citations · 260 across the 17 of their papers we have counts for
3 papers · 1 filter
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone
Edresson Casanova, Julian Weber, Christopher Shulby +3
YourTTS brings the power of a multilingual approach to the task of zero-shot multi-speaker TTS. Our method builds upon the VITS model and adds several novel modifications for zero-…
Training Deep Networks from Zero to Hero: avoiding pitfalls and going beyond
Moacir Antonelli Ponti, Fernando Pereira dos Santos, Leo Sampaio Ferraz Ribeiro +1
Training deep neural networks may be challenging in real world data. Using models as black-boxes, even with transfer learning, can result in poor generalization or inconclusive res…
SC-GlowTTS: an Efficient Zero-Shot Multi-Speaker Text-To-Speech Model
Edresson Casanova, Christopher Shulby, Eren Gölge +6
In this paper, we propose SC-GlowTTS: an efficient zero-shot multi-speaker text-to-speech model that improves similarity for speakers unseen during training. We propose a speaker-c…