This project is an end-to-end text-to-speech engine and deep learning voice synthesizer. It functions as a neural speech synthesis framework that converts written text directly into audio waveforms using a single neural network.
The system implements an adversarial framework and a conditional variational autoencoder to generate high-fidelity artificial speech. It utilizes a generative adversarial network to ensure synthesized audio is indistinguishable from real human speech.
The toolkit provides capabilities for neural speech synthesis, text-to-audio generation, and the training of custom voice models using specific voice datasets.