# mozilla/tts **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/mozilla-tts).** 10,151 stars · 1,324 forks · Jupyter Notebook · MPL-2.0 ## Links - GitHub: https://github.com/mozilla/TTS - awesome-repositories: https://awesome-repositories.com/repository/mozilla-tts.md ## Topics `dataset-analysis` `deep-learning` `gantts` `glow-tts` `melgan` `multiband-melgan` `python` `pytorch` `speaker-encoder` `speech` `tacotron` `tacotron2` `tensorflow2` `text-to-speech` `tts` `vocoder` ## Description This project is a comprehensive suite for neural speech synthesis, featuring a deep learning text-to-speech engine, a neural speech synthesis trainer, and a voice cloning toolkit. It provides a system for synthesizing human-like speech from text using neural network models and high-fidelity vocoders. The suite includes a speech model conversion utility to transform deep learning models between different formats for deployment across various hardware runtimes. It also provides a self-contained HTTP server to expose pre-trained text-to-speech models as a remote audio API. Capabilities include custom speech model training with hardware acceleration, speaker embedding computation for voice cloning, and the transformation of spectrograms into raw waveforms for high-fidelity audio generation. The project also provides utilities for speech dataset curation. ## Tags ### Artificial Intelligence & ML - [Speech Synthesis Models](https://awesome-repositories.com/f/artificial-intelligence-ml/speech-synthesis-models.md) — Provides generative neural network architectures that convert text input into realistic human speech. - [Text-to-Speech Synthesis](https://awesome-repositories.com/f/artificial-intelligence-ml/text-to-speech-synthesis.md) — Offers a deep learning engine that converts written text into human-like audible speech across multiple languages. ([source](https://github.com/mozilla/tts#readme)) - [Neural Vocoders](https://awesome-repositories.com/f/artificial-intelligence-ml/audio-tokenization/waveform-decoders/neural-vocoders.md) — Transforms intermediate frequency-based spectrograms into raw audio waveforms to produce high-fidelity human speech. - [Neural Text-to-Speech Engines](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/speech-synthesis/neural-text-to-speech-engines.md) — Implements deep learning pipelines that generate synthetic speech by modeling specific vocal characteristics. - [Text-to-Speech Model Training](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-training-and-tuning/training-frameworks/model-training-frameworks/text-to-speech-model-training.md) — Provides a comprehensive framework for training generative text-to-speech models using audio-text pairs and hardware acceleration. ([source](https://github.com/mozilla/tts#readme)) - [Speaker Embeddings](https://awesome-repositories.com/f/artificial-intelligence-ml/speaker-embeddings.md) — Generates numerical representations of vocal characteristics to enable voice cloning and multi-speaker synthesis. ([source](https://github.com/mozilla/tts#readme)) - [Training Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/speech-synthesis-models/training-frameworks.md) — Ships a framework for training and fine-tuning speech models using custom datasets and hardware acceleration. - [Voice Cloning](https://awesome-repositories.com/f/artificial-intelligence-ml/voice-cloning.md) — Replicates specific human vocal characteristics from audio samples to synthesize mimicking speech. ([source](https://github.com/mozilla/TTS/wiki/Released-Models)) - [Voice Cloning Toolkits](https://awesome-repositories.com/f/artificial-intelligence-ml/voice-cloning-toolkits.md) — Offers a collection of utilities for capturing and applying vocal characteristics to mimic specific voices. - [Cross-Framework Model Conversion](https://awesome-repositories.com/f/artificial-intelligence-ml/cross-framework-model-conversion.md) — Translates trained neural network weights between different deep learning formats for cross-runtime compatibility. - [Custom Model Training](https://awesome-repositories.com/f/artificial-intelligence-ml/custom-model-training.md) — Fine-tunes generative speech models on specialized datasets to achieve precise pronunciation and voice mimicry. ([source](https://github.com/mozilla/TTS/wiki/TTS-Notebooks-and-Tutorials)) - [Model Inference Servers](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-inference-serving/engines-runtimes-servers/model-inference-servers.md) — Implements a dedicated server application to host machine learning models for network-accessible audio synthesis. - [Model Export Formats](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-optimization-and-inference/serving-and-runtime/inference-optimization-utilities/model-export-formats.md) — Converts trained models into standard industry formats to enable deployment across diverse hardware devices. ([source](https://github.com/mozilla/tts#readme)) - [Model Conversion Utilities](https://awesome-repositories.com/f/artificial-intelligence-ml/model-conversion-utilities.md) — Provides utilities to transform model weights and architectures between different file formats and runtimes. - [Hardware Acceleration](https://awesome-repositories.com/f/artificial-intelligence-ml/model-training/hardware-acceleration.md) — Uses specialized graphics or tensor hardware to accelerate the computationally intensive training of speech models. - [Self-Hosted Synthesis Servers](https://awesome-repositories.com/f/artificial-intelligence-ml/text-to-speech/local-speech-synthesis/self-hosted-synthesis-servers.md) — Provides a self-contained HTTP server to host and serve text-to-speech models on private infrastructure. ([source](https://github.com/mozilla/TTS/wiki/Released-Models)) ### Graphics & Multimedia - [High-Fidelity Speech Synthesis](https://awesome-repositories.com/f/graphics-multimedia/audio-music/audio-playback/high-fidelity-audio-streaming/high-fidelity-speech-synthesis.md) — Implements high-fidelity neural vocoders to transform spectrograms into natural-sounding raw audio waveforms. ([source](https://github.com/mozilla/TTS/wiki/Released-Models)) ### DevOps & Infrastructure - [Model Conversion](https://awesome-repositories.com/f/devops-infrastructure/model-conversion.md) — Transforms trained models between different deep learning frameworks to ensure cross-environment compatibility. ([source](https://github.com/mozilla/TTS/wiki/TTS-Notebooks-and-Tutorials)) - [TTS Service Hosting](https://awesome-repositories.com/f/devops-infrastructure/speech-service-deployments/tts-service-hosting.md) — Runs a self-contained HTTP server to expose pre-trained speech models as a web service. ### Part of an Awesome List - [Natural Language Processing](https://awesome-repositories.com/f/awesome-lists/ai/natural-language-processing.md) — Deep learning models for text-to-speech synthesis. - [Speech and Audio](https://awesome-repositories.com/f/awesome-lists/ai/speech-and-audio.md) — Deep learning framework for text-to-speech. - [Speech and Audio Processing](https://awesome-repositories.com/f/awesome-lists/ai/speech-and-audio-processing.md) — Deep learning toolkit for text-to-speech.