tacotron2
DiffSinger
tacotron2 | DiffSinger | |
---|---|---|
29 | 1 | |
4,912 | 223 | |
0.9% | - | |
0.0 | 10.0 | |
5 months ago | over 2 years ago | |
Jupyter Notebook | Python | |
BSD 3-clause "New" or "Revised" License | MIT License |
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tacotron2
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ESpeak-ng: speech synthesizer with more than one hundred languages and accents
The quality also depends on the type of model. I'm not really sure what ESpeak-ng actually uses? The classical TTS approaches often use some statistical model (e.g. HMM) + some vocoder. You can get to intelligible speech pretty easily but the quality is bad (w.r.t. how natural it sounds).
There are better open source TTS models. E.g. check https://github.com/neonbjb/tortoise-tts or https://github.com/NVIDIA/tacotron2. Or here for more: https://www.reddit.com/r/MachineLearning/comments/12kjof5/d_...
- [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)
DiffSinger
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[D] What is the best open source text to speech model?
DiffTTS (DiffSinger) submitted: Apr 3, 2021 paper: https://arxiv.org/pdf/2104.01409v1.pdf github: https://github.com/keonlee9420/DiffSinger
What are some alternatives?
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
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.
Voice-Cloning-App - A Python/Pytorch app for easily synthesising human voices
tacotron - A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
Speech-Backbones - This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
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
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)
flowtron - Flowtron is an auto-regressive flow-based generative network for text to speech synthesis with control over speech variation and style transfer
waveglow - A Flow-based Generative Network for Speech Synthesis
vits - VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech