framework-reproducibility
Real-Time-Voice-Cloning
framework-reproducibility | Real-Time-Voice-Cloning | |
---|---|---|
5 | 96 | |
418 | 50,951 | |
1.2% | - | |
5.8 | 0.0 | |
7 months ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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framework-reproducibility
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Tensorflow: I'm getting different results from the same code depending on where I run it. [D]
Even with a fixed seed there's no guarantee that you'll get the exact same results due to the fact that most floating operations are not deterministic when parallelized. You can enable determinism flags in your framework to try and mitigate that, but results may still vary depending on your model and how you're running it.
- Same seed, different images
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Dealing with non-deterministic result
Setting the seed alone is not enough because there will be a randomness resulted from GPU operations (there is some way to eliminate randomness due to GPU operations like https://github.com/NVIDIA/framework-determinism, but I cannot make it work with the current latest version of TF). Another workaround is not using GPU, but the training time does not make sense as I need to iterate fast, trying new idea.
- No Bee, it's you...
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[D] Do you yourself write 100% reproducible ML code?
check out https://github.com/NVIDIA/framework-determinism, which should allow you to make fully reproducible to the bit code that runs on GPU. i've contributed to this repo and the author is extremely helpful.
Real-Time-Voice-Cloning
- FLaNK Stack Weekly 12 February 2024
- Voice Cloning
- Show HN: Real Time Voice Cloning – Instant DeepFake Audio
- Bu dakikadaki bahsedilen yapay zekayı bulamadım yardımcı olur musunuz?
- Alarming Rise of Voice Cloning Fraud Targeting the Elderly through AI
- Dark Brandon going hard
- Conselho do TRF-4 afasta juiz da Lava Jato
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What Photoshop Can't Do, DragGAN Can! See How! Paper Explained, Along with Additional Supplementary Video Footage
Oh maybe it is available: https://github.com/CorentinJ/Real-Time-Voice-Cloning
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Regarding recent posts about AI voice generation
I know this isn't the bulk of your argument, but if the concern is uploading, offline voice cloners have existed for years (albeit not as good as elevenlabs) but will presumably get far better in the years to come now that everyone has seen what's possible and as PC compute power continues to improve. https://github.com/CorentinJ/Real-Time-Voice-Cloning
- 'He Would Still Be Here': Man Dies by Suicide After Talking with AI Chatbot, Widow Says | The incident raises concerns about guardrails around quickly-proliferating conversational AI models.
What are some alternatives?
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
DeepFaceLab - DeepFaceLab is the leading software for creating deepfakes.
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
MockingBird - 🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time
silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
glados-voice-assistant - DIY Voice Assistant based on the GLaDOS character from Portal video game series. Works with home assistant!
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)
RHVoice - a free and open source speech synthesizer for Russian and other languages
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
tacotron2 - Tacotron 2 - PyTorch implementation with faster-than-realtime inference