hifi-gan
tacotron2
| hifi-gan | tacotron2 | |
|---|---|---|
| 5 | 28 | |
| 1,764 | 4,901 | |
| - | 0.5% | |
| 0.0 | 0.0 | |
| 9 months ago | 4 months ago | |
| Python | Jupyter Notebook | |
| MIT License | BSD 3-clause "New" or "Revised" License |
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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.)
tacotron2
- [D] What is the best open source text to speech model?
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[D] The model used in the AI generated Jay-z vocals
Which might use https://github.com/NVIDIA/tacotron2 in their backend
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Can anyone reccomend any free voice cloning software/websites even if it provided limited word options
One thing is uberduck.ai but I think it's freemium (it's free but some features are premium). There's also tacotron 2.0 and its pytorch page. Many other softwares on sub but tacotron gave this and this and this.
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Sauron be spitting bars
Maybe we can use AI to hear this rapped by a famous rapper?
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Kerfuś
Sadly GothicBot the TTS I knew, doesn't exist anymore, but here is an alternative. It works in polish from what I heard.
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How far are we from being able to clone a singers voice?
From what I’ve seen, NVIDIA’s Tacotron2 can already be used to create some pretty convincing singing.
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Is it possible to make compelling synthesized speech with fairly low-quality recordings?
You might want to try something like Tacotron 2 by Nvidia to experiment with your current data.
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What voice-changing apps are available right now?
We have the TorToiSe repo, the SV2TTS repo, and from here you have the other models like Tacotron 2, FastSpeech 2, and such. A there is a lot that goes into training a baseline for these models on the LJSpeech and LibriTTS datasets. Fine tuning is left up to the user.
- The OG (OC)
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XQC Falls for dono thinkng its Adept
I had tried tacotron2 + waveglow and it's quite easy to get very good results. The hardest part is collecting clean data.
What are some alternatives?
WaveRNN - WaveRNN Vocoder + TTS
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
wavegrad - A fast, high-quality neural vocoder.
Voice-Cloning-App - A Python/Pytorch app for easily synthesising human voices
Parallel-Tacotron2 - PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
diffwave - DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
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)
waveglow - A Flow-based Generative Network for Speech Synthesis