MelGAN
MelGAN is a neural vocoder designed for efficient and high-quality speech synthesis. It utilizes generative adversarial networks to convert mel-spectrograms into audio waveforms in real-time.
speech synthesis
Zero-shot TTS (voice cloning)
Zero-shot TTS (voice cloning) is a speech synthesis technique that enables generating natural-sounding speech in a new speaker’s voice without requiring prior training on that speaker’s data. It leverages machine learning models to generalize across voices, enabling rapid voice cloning from minimal audio samples.
WaveGlow
WaveGlow is a flow-based generative model designed for high-quality speech synthesis. It combines normalizing flows with a neural network architecture to generate audio waveforms directly from mel-spectrograms.
Tacotron
Tacotron is a neural network architecture designed for text-to-speech synthesis, generating natural-sounding speech directly from text input. Developed by Google researchers, it represents a significant advancement in end-to-end speech synthesis systems.
Coqui TTS (open-source TTS)
Coqui TTS is an open-source text-to-speech synthesis system designed to provide accessible, high-quality speech generation through deep learning models. It supports multiple languages and voices, emphasizing community collaboration and transparency in speech technology development.
Neural voice cloning
Neural voice cloning is a technology that uses deep learning to replicate a person’s voice by generating synthetic speech that closely mimics the original speaker’s vocal characteristics. It enables the creation of personalized speech synthesis with relatively small amounts of audio data.
Text-to-speech synthesis
Text-to-speech synthesis is a technology that converts written text into spoken voice output. It is used in various applications to improve accessibility, provide voice interaction, and automate speech generation.
Few-shot TTS (text-to-speech)
Few-shot text-to-speech (TTS) is an advanced approach in speech synthesis that enables the creation of natural-sounding voice models using only a small amount of reference audio data. This technique aims to generate high-quality speech in a target speaker’s voice after exposure to limited examples, facilitating rapid adaptation to new voices with minimal data.
WaveNet
WaveNet is a deep generative model for raw audio waveforms developed by DeepMind, known for producing highly realistic speech and audio synthesis through neural network architectures.
HiFi-GAN
HiFi-GAN is a deep learning-based neural vocoder designed for high-fidelity speech synthesis. It uses generative adversarial networks to efficiently produce natural-sounding audio waveforms from mel-spectrograms.