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| Name | Deep Learning In Audio for Absolute Beginners: From No Experience & No Datasets to a Deployed Model |
| Video Uploader | Video From ADC - Audio Developer Conference |
| Upload Date | This Video Uploaded At 16-06-2023 14:00:07 |
| Video Discription | This video has been re-uploaded due to an error in the original https://audio.dev/ -- @audiodevcon Jumpstart Guide to Deep Learning In Audio for Absolute Beginners: From No Experience and No Datasets to a Deployed Model - Jan Wilczek - ADC22 Deep learning is becoming more and more significant in all areas of science including audio processing. Yet a lot of people have a hard time understanding it or are too scared to start learning it altogether. Is deep learning really so difficult that you need a PhD to use it? Does it truly require huge datasets and gigantic computational clusters? Is it possible to deploy neural networks in real-time audio plugins? In this talk, I will show you how you can learn deep learning for Virtual Analog modeling of audio effects fast, for free, without a PhD, without any special equipment or loads of data, and deploy your deep learning model in an audio plugin. What you will learn: - what are the 4 biggest myths concerning deep learning? - how to learn deep learning for audio fast in 4 simple steps for free - where to find and how to synthesize a dataset to model your analog device of choice - how to train your first deep learning model for audio using the basics of PyTorch and without a computational cluster - how to deploy your model in a real-time audio plugin The presentation will feature a live demo of setting up a deep learning pipeline and training a neural network for Virtual Analog modeling of a distortion effect. Slides: link will be updated when available. _ Jan Wilczek I am an Audio Developer of Music Maker JAM at Loudly GmbH in Berlin; an app to make loop-based music that runs on Android, iOS, and Windows. Additionally, I have created https://TheWolfSound.com to help students and software engineers learn audio programming for getting game audio, audio plugin, or mobile audio developer jobs. I am also a researcher in the area of Virtual Analog modeling using deep learning; my latest work was presented at the Digital Audio FX 2022 conference in Vienna. My professional goal is to lower the entry barrier for everyone interested in audio. I pursue it by publishing high-quality articles, videos, and podcasts or... speaking at conferences. _ Streamed & Edited by Digital Medium Ltd - online.digital-medium.co.uk _ Organized and produced by JUCE: https://juce.com/ _ Special thanks to the ADC22 Team: Lina Berzinskas Sophie Carus Derek Heimlich Andrew Kirk Bobby Lombardi Tom Poole Ralph Richbourg Jim Roper Jonathan Roper #audiodevcon #audiodev #deeplearning [sqrah49GUkI] |
| Category | Science & Technology |
| Tags | Deep Learning In Audio | audio deep learning | juce deep learning tutorial | Jan Wilczek | neural networks in real-time audio plugins | beginners guide to deep learning in audio | audio deep learning made simple | audio deep learning models | deep learning model in an audio plugin | PyTorch | adc deep learning | ADC | audio developer | audio dev | audio programming | audio programmer | sound dev | JUCE | ADC22 | audio processing | deep learning for Virtual Analog modeling of audio effects | ADC talks |
