STYLER
hifi-gan
| STYLER | hifi-gan | |
|---|---|---|
| 3 | 5 | |
| 150 | 1,764 | |
| - | - | |
| 1.8 | 0.0 | |
| over 2 years ago | 9 months ago | |
| Python | Python | |
| MIT License | MIT License |
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STYLER
- [D] What is the best open source text to speech model?
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STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech
demo: https://keonlee9420.github.io/STYLER-Demo/
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[R] STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech
code: https://github.com/keonlee9420/STYLER
hifi-gan
- [D] What is the best open source text to speech model?
- I made Lisa-nee TTS (Imai Lisa)
- HiFi-GAN: Generative Adversarial Networks for Efficient and Hi-Fi Speech Synth
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[2108.13320] Neural HMMs are all you need (for high-quality attention-free TTS)
It will be interesting to see if the artefacts you noticed persist once we've trained the model for longer and switch to a better vocoder such as HiFi-GAN. (The paper and audio examples use WaveGlow since that's the default of the repository we compared ourselves to.) That said, "choppiness" sounds to me like it might be related to the temporal evolution, in which case it's something that a non-causal, convolutional post-net might be able to smooth over.
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The dangers of AI
Hey, as far as I know this paper is the current SoTA on public data that is open source. Github is here. If you are interested in really getting into speech synthesis, this page has everything (modern stuff on the bottom.)
What are some alternatives?
waveglow - A Flow-based Generative Network for Speech Synthesis
WaveRNN - WaveRNN Vocoder + TTS
radtts - Provides training, inference and voice conversion recipes for RADTTS and RADTTS++: Flow-based TTS models with Robust Alignment Learning, Diverse Synthesis, and Generative Modeling and Fine-Grained Control over of Low Dimensional (F0 and Energy) Speech Attributes.
wavegrad - A fast, high-quality neural vocoder.
flowtron - Flowtron is an auto-regressive flow-based generative network for text to speech synthesis with control over speech variation and style transfer
Parallel-Tacotron2 - PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Speech-Backbones - This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.
diffwave - DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.
tacotron - A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
DiffSinger - PyTorch implementation of DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism (focused on DiffSpeech)
TensorFlowTTS - :stuck_out_tongue_closed_eyes: TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, French, Korean, Chinese, German and Easy to adapt for other languages)