Tacotron-2 and Tacotron-pytorch
These are competing implementations of the same Tacotron text-to-speech architecture in different deep learning frameworks (TensorFlow vs PyTorch), allowing users to choose based on their preferred framework rather than using them together.
About Tacotron-2
Rayhane-mamah/Tacotron-2
DeepMind's Tacotron-2 Tensorflow implementation
This project helps generate natural-sounding speech from written text. You provide text as input, and it produces an audio file of that text spoken aloud. It's designed for researchers and developers working on advanced text-to-speech systems who need to experiment with and build upon state-of-the-art neural network architectures.
About Tacotron-pytorch
soobinseo/Tacotron-pytorch
Pytorch implementation of Tacotron
This project helps machine learning engineers and researchers implement a text-to-speech model. It takes a collection of text scripts and corresponding audio files as input, processes them, and then trains a model that can convert new text into synthesized speech. The primary users are those working on speech synthesis research or building custom voice generation systems.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work