🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

🤖 💬 Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)

Speaker embedding (d-vector) trained with GE2E loss

zero-shot realtime TTS system, fully offline, free and open source

[InterSpeech 2020] "Improving the Speaker Identity of Non-Parallel Many-to-Many VoiceConversion with Adversarial Speaker Recognition" by Shaojin Ding, Guanlong Zhao, Ricardo Gutierrez-Osuna

🎤 Create high-quality text-to-speech audio using FastSpeech 2 in PyTorch. Easily customize for English and Mandarin with multi-speaker support.

Create fast, lightweight text-to-speech audio on your CPU with MioTTS-llama.cpp. Convert text to WAV files using customizable voice options.

Real-Time-Voice-Cloning using Generative Adversarial Networks. It combines text and speaker and generates natural sounding audio. Some Traditional Methods like Convolutional Neural Networks can contain some limitation it requires large datasets and lengthy processing time, to overcome these limitations we are using GANs to maximize space use.

Generate zero-shot multilingual TTS nodes for ComfyUI with voice cloning and voice design, supporting 600+ languages

Run pure C inference for Mistral Voxtral-4B-TTS with mmap safetensors, BF16 weights, and 24kHz WAV output.