TensorFlowTTS is a state-of-the-art, open-source speech synthesis library built on TensorFlow 2. It offers a variety of architectures for text-to-speech, including classic and modern models such as Tacotron‑2, FastSpeech / FastSpeech2, and neural vocoders like MelGAN and Multiband‑MelGAN. Because it’s based on TensorFlow 2, it can leverage optimizations such as fake-quantization aware training and pruning — which allow models to run faster than real time and to be deployable on mobile or embedded platforms. The library supports multiple languages (English, French, Korean, Chinese, German, etc.) and is relatively easy to adapt to new languages. With integrated vocoder + mel-spectrogram generation pipelines, pre-trained models, and fairly flexible architecture, TensorFlowTTS is a great off-the-shelf and extensible TTS engine for applications ranging from voice assistants to content generation or accessibility tools.
Features
- Multiple TTS architectures: Tacotron-2, FastSpeech / FastSpeech2, etc.
- Neural vocoders included (MelGAN, Multiband-MelGAN) for waveform generation
- Real-time or faster-than-real-time inference with TensorFlow 2 optimizations (quantization, pruning)
- Multi-language support (English, French, Korean, Chinese, German, and potentially more)
- Easy to extend or fine-tune for new languages or custom voices
- Deployable on mobile devices or embedded systems thanks to efficient inference