keonlee9420/Comprehensive-Tacotron2

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MIT License
Created almost 3 years ago
Updated 9 months ago

keonlee9420/Comprehensive-Tacotron2

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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.

PortaSpeech

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

Comprehensive-Transformer-TTS

A Non-Autoregressive Transformer based Text-to-Speech, 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

DiffGAN-TTS

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

Expressive-FastSpeech2

PyTorch Implementation of Non-autoregressive Expressive (emotional, conversational) TTS based on FastSpeech2, supporting English, Korean, and your own languages.

DiffSinger

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

Parallel-Tacotron2

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

StyleSpeech

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

DailyTalk

Official repository of DailyTalk: Spoken Dialogue Dataset for Conversational Text-to-Speech, ICASSP 2023 (Oral)

Cross-Speaker-Emotion-Transfer

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

STYLER

Official repository of STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech, INTERSPEECH 2021

Comprehensive-E2E-TTS

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

Soft-DTW-Loss

PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA

FastPitchFormant

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

VAENAR-TTS

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

WaveGrad2

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

Daft-Exprt

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

Robust_Fine_Grained_Prosody_Control

PyTorch Implementation of Robust and fine-grained prosody control of end-to-end speech synthesis

Stepwise_Monotonic_Multihead_Attention

PyTorch Implementation of Stepwise Monotonic Multihead Attention similar to Enhancing Monotonicity for Robust Autoregressive Transformer TTS

Deep-Learning-TTS-Template

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

tacotron2_MMI

Another PyTorch implementation of Tacotron2 MMI (with waveglow) which supports n_frames_per_step>1 mode(reduction windows) and diagonal guided attention for robust alignments.

Jupyter Notebook

Fully_Hierarchical_Fine_Grained_TTS

Pytorch Implementation of Fully-hierarchical fine-grained prosody modeling for interpretable speech synthesis (Unofficial)

cs231n

cs231n 2020 Spring assignments implementation

Jupyter Notebook

pintos

KAIST CS330 OS pintos Project