jaywalnut310/vits

Features

• Text-to-Speech Engines - Provides a full text-to-speech engine that converts written text into natural-sounding human speech.
• Deep Learning Audio Libraries - Functions as a deep learning audio library for training high-fidelity speech models from text and audio.
• End-to-End Speech Synthesis - Integrates text analysis, acoustic modeling, and waveform generation into a single differentiable neural pipeline.
• Text-to-Speech Model Training - Provides the capabilities to train generative speech models using audio-text datasets.
• Voice Synthesizer Training - Supports training voice synthesizers to mimic specific vocal characteristics and linguistic patterns.
• Speech Synthesis Models - Utilizes generative neural network architectures to produce high-quality, fluid artificial speech.
• Waveform Decoders - Uses a convolutional waveform decoder to transform latent representations into high-fidelity raw audio samples.
• TTS Adversarial Frameworks - Uses an adversarial framework to improve the audio quality and realism of synthesized speech.
• Variational Autoencoders - Implements a conditional variational autoencoder to map text sequences to a latent space for natural speech variation.
• Conditional VAE Speech Models - Employs a conditional variational autoencoder to generate natural-sounding human voices.
• Generative Adversarial Networks - Employs a generative adversarial network with a discriminator to ensure synthesized audio is indistinguishable from human speech.
• Prosodic Duration Predictors - Includes a stochastic duration predictor to model the natural variability of speech timing by sampling from a distribution.
• Text-to-Audio Synthesis - Automates the generation of audio files from text scripts using neural synthesis.
• Monotonic Alignment Searches - Automatically learns the alignment and duration between text characters and audio frames without external tools.

Star history