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Search results for text to speech neural tts

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16 search results found

Cognitive Speech Tts ⭐ 775

Microsoft Text-to-Speech API sample code in several languages, part of Cognitive Services.

Portaspeech ⭐ 211

PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech

Comprehensive Transformer Tts ⭐ 146

A Non-Autoregressive Transformer based TTS, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate TTS.

Cross Speaker Emotion Transfer ⭐ 104

PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech

Stylespeech ⭐ 103

Official implementation of Meta-StyleSpeech and StyleSpeech

Stylespeech ⭐ 100

PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation

Diffsinger ⭐ 85

PyTorch implementation of DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism (focused on DiffSpeech)

Parallel Tacotron2 ⭐ 80

PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Comprehensive E2e Tts ⭐ 71

A Non-Autoregressive End-to-End Text-to-Speech (text-to-wav), supporting a family of SOTA unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate E2E-TTS

Diffgan Tts ⭐ 52

PyTorch Implementation of DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs

Daft Exprt ⭐ 36

PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis

Wavegrad2 ⭐ 35

PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis

Vaenar Tts ⭐ 25

PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

Comprehensive Tacotron2 ⭐ 23

PyTorch Implementation of Google's Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. This implementation supports both single-, multi-speaker TTS and several techniques to enforce the robustness and efficiency of the model.

Fastpitchformant ⭐ 21

PyTorch Implementation of NCSOFT's FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis

A cross-platform engine for neural TTS models.

Deep Learning Tts Template ⭐ 8

This is a template for the Non-autoregressive Deep Learning-Based TTS model (in PyTorch).

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