hifi-gan
TransformerTTS
| hifi-gan | TransformerTTS | |
|---|---|---|
| 5 | 1 | |
| 1,764 | 1,099 | |
| - | 1.4% | |
| 0.0 | 0.0 | |
| 9 months ago | about 1 month ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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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.)
TransformerTTS
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Good text-to-speech models/audio filters
I've already explored many models, for example: https://github.com/as-ideas/TransformerTTS This one sounds ok, the model attention to pauses, punctuation marks is normal, but I want to get better accent placement.
What are some alternatives?
WaveRNN - WaveRNN Vocoder + TTS
tacotron - A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)
wavegrad - A fast, high-quality neural vocoder.
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Parallel-Tacotron2 - PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Voice-Cloning-App - A Python/Pytorch app for easily synthesising human voices
diffwave - DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.
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)
mlp-singer - Official implementation of MLP Singer: Towards Rapid Parallel Korean Singing Voice Synthesis (IEEE MLSP 2021)
so-vits-svc-fork - so-vits-svc fork with realtime support, improved interface and more features.
voice100 - Voice100 includes neural TTS/ASR models. Inference of Voice100 is low cost as its models are tiny and only depend on CNN without autoregression.