NVIDIA/tacotron2

Health v2 · maintenance only

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5296 stars · 1410 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

NVIDIA's PyTorch implementation of the Tacotron 2 text-to-speech model, which synthesizes mel spectrograms from text for vocoder-based audio generation. It supports distributed training, automatic mixed precision, and faster-than-realtime inference when paired with vocoders like WaveGlow.

Use cases

• convert text to speech audio in Python
• train a custom TTS model on my own dataset
• generate speech from text with a pretrained model
• fine-tune Tacotron 2 on LJSpeech
• run faster-than-realtime neural speech synthesis on GPU
• build a voice synthesis pipeline with PyTorch

When to choose

• you need a well-tested PyTorch Tacotron 2 implementation with pretrained checkpoints
• you want GPU-accelerated training with mixed precision and multi-GPU support
• you are doing research or experimentation with neural TTS on NVIDIA hardware

When to avoid

• you need the latest state-of-the-art TTS models (e.g., VITS, modern diffusion-based TTS)
• you have no NVIDIA GPU, since CUDA cuDNN is required
• you want a production-ready TTS service with an API out of the box

Facets

library · maturity maintenance

tts deep-learning machine-learning speech-processing deep-learning artificial-intelligence python windows pytorch tacotron2 speech-synthesis ljspeech nvidia text-to-speech waveglow gpu linux

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markdown · JSON · MCP: product_card(name="NVIDIA/tacotron2")