Ryan Prenger @DeepPrenger
Senior Deep Learning Researcher at NVIDIA Joined April 2009-
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Following83
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Try Googling "Who played Glinda in the Wizard of Oz"
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Ryan Prenger retweeted
Here's a Secret: #startups are Brutal Please RT to spread the word on my FIRST @Inc column inc.com/gavi-begtrup/h…
I'm tearing up a little bit.
Ryan Prenger retweeted
We’ve had a dream for many years of a TTS engine with enough emotional range to do voice acting. We’re incredibly proud to unveil Flowtron, the TTS narrating the 2020 I AM AI video. Take a listen: youtu.be/bOf2S7OzFEg?t=…
Ryan Prenger retweeted
We finally shared a Mellotron model pre-trained on LJS for our essential artistic needs :) github.com/NVIDIA/mellotr…
Ryan Prenger retweeted
@angaidh_ @benrileysmith
Ryan Prenger retweeted
Very often I'd turn around from my desk to be delighted with blowing examples from Deep Learning Super Sampling 2.0! Definitely a game changer! DLSS 2.0 is "a model to rule them all", just like WaveGlow! Take a look and compare DLSS with other methods!
Very often I'd turn around from my desk to be delighted with blowing examples from Deep Learning Super Sampling 2.0! Definitely a game changer! DLSS 2.0 is "a model to rule them all", just like WaveGlow! Take a look and compare DLSS with other methods!
Ryan Prenger retweeted
Celebrate WaveGlow's anniversary with us! Listen to our new samples and download our new model weights with higher audio quality and higher throughput. WaveGlow latest implementation produces audio samples at a rate of 4850 kHz! 😱 github.com/NVIDIA/waveglo…
Ryan Prenger retweeted
The stable release of @PyTorch 1.0 is here! A big thank you to the community that's formed around #PyTorch and to those contributing with code, feedback, or new projects. Learn how to get started here: code.fb.com/ai-research/py…
Ryan Prenger retweeted
Image padding causes small but measurable artifacts for CNNs. Partial convolution padding improves ResNet-50 Top1 by 0.478% on average, and improves semantic segmentation results on image borders. Paper by @GuilinL: arxiv.org/pdf/1811.11718… Code: github.com/NVIDIA/partial…
Ryan Prenger retweeted
We have published our Tacotron 2 and WaveGlow trained model! Visit our repository github.com/NVIDIA/tacotro… to check out our text-to-speech synthesis demo and build your own high quality TTS models with faster than real-time inference!
Ryan Prenger retweeted
A good explanation of how WaveGlow works. Note that our inference speed is now 1200 kHz. 🔥
A good explanation of how WaveGlow works. Note that our inference speed is now 1200 kHz. 🔥
Ryan Prenger retweeted
WaveGlow inference: now faster! We improved mel-spectrogram inversion speed from 500 kHz to 1200 kHz on a single V100 GPU. The model is the same, just implemented better. More to come! github.com/NVIDIA/waveglow
Ryan Prenger retweeted
We just open-sourced a suite of ODE solvers in PyTorch: github.com/rtqichen/torch… Everything happens on the GPU and is differentiable. Now you can use ODEs in your deep learning models! Credit to @rtqichen.
Ryan Prenger retweeted
WaveGlow: A Flow-based Generative Network for Speech Synthesis By NVIDIA (@DeepPrenger @RafaelValleArt @ctnzr) Generates HQ speech from mel-spectrograms 25x faster than real time on V100 GPU PyTorch + Pretrained github.com/NVIDIA/waveglow ArXiv arxiv.org/abs/1811.00002
Ryan Prenger retweeted
Very excited that our Applied Deep Learning Research (ADLR) team at #NVIDIA has released code for WaveGlow. Let's get our #GPUs and build text-to-speech systems running at the speed of light! #DeepLearning github.com/NVIDIA/waveglow
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