r9y9/deepvoice3_pytorch

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1975 stars · 481 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch implementation of Deep Voice 3 and related convolutional neural network-based text-to-speech synthesis models. It includes training code, dataset preprocessors (LJSpeech, JSUT, VCTK), language-dependent text frontends for English and Japanese, and pre-trained single- and multi-speaker models.

Use cases

• train a text-to-speech model in pytorch
• synthesize speech from text with deep voice 3
• build a multi-speaker tts model on vctk
• convert text to speech for english and japanese
• experiment with convolutional sequence-to-sequence tts models
• fine-tune a pretrained tts model on a custom dataset

When to choose

• you want a research-grade PyTorch implementation of Deep Voice 3
• you need single- or multi-speaker TTS training on LJSpeech, JSUT, or VCTK
• you want pretrained models and audio sample references for TTS experiments

When to avoid

• you need a production-ready, actively maintained TTS system
• you want the latest state-of-the-art neural TTS architectures
• you need a simple plug-and-play TTS API without training

Facets

library · maturity maintenance

tts machine-learning deep-learning nlp speech-processing machine-learning deep-learning python pytorch deep-voice-3 speech-synthesis multi-speaker ljspeech vctk convolutional-sequence-learning audio linux macos gpu

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