AI Voice & Text-to-Speech Models

Latent-diffusion model for general-purpose text-to-audio. Generates speech, music, and sound effects with a unified prior.

Resemble AI's open Chatterbox TTS. Zero-shot voice cloning from a short audio prompt with an exaggeration control for emotion intensity, plus CFG weight to balance pacing and fidelity.

Open-weights 82M-parameter TTS. Punches above its size class on naturalness benchmarks at a fraction of the inference cost of larger models.

OpenAI's text-to-speech model. Six built-in voices with natural intonation.

OpenAI's high-definition TTS model. Better quality for production use cases.

MyShell OpenVoice v2. Multilingual zero-shot voice cloning with accurate tone-color reproduction and style/emotion control.

Hugging Face Parler-TTS Mini. Lightweight TTS conditioned on a natural-language style description for fine-grained control over voice characteristics.

A unified Text-to-Speech demo featuring three powerful modes: Voice, Clone and Design

Stable-Diffusion-based real-time music generator. Operates on spectrogram images then resynthesizes audio, enables seamless transitions and looping.

Retrieval-based Voice Conversion. Converts a source recording into a target speaker's voice, preserving pitch, prosody and rhythm.

Spark efficient TTS with disentangled control over speaker, content and style. Strong cross-lingual zero-shot performance.

Style-based TTS using diffusion and adversarial training. Human-level naturalness in zero-shot voice synthesis from a 3-5s reference clip.

Suno's text-prompted generative audio model. Speech, music, ambient sound and effects with non-verbal cues like laughter or sighs.

Multi-voice expressive TTS. Slow but high-quality with strong prosody and natural intonation. Trained for long-form narration use cases.