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We propose 🍵 Matcha-TTS, a new approach to non-autoregressive neural TTS, that uses conditional flow matching (similar to rectified flows) to speed up ODE-based speech synthesis. Our method:
-* Is probabilistic
-* Has compact memory footprint
-* Sounds highly natural
-* Is very fast to synthesise from
-
+- Is probabilistic
+- Has compact memory footprint
+- Sounds highly natural
+- Is very fast to synthesise from
Check out our [demo page][this_page]. Read our [arXiv preprint for more details][arxiv_link].
Code is available in our [GitHub repository][github_link], along with pre-trained models.
@@ -225,9 +224,9 @@ audio {
-## Architecture
+