Join Us For ADC23 - London - 13-15 November 2023
More Info: https://audio.dev/
@audiodevcon
Designing Smart Algorithms with Traditional DSP vs. Machine Learning - Amit Shoham - ADCx SF
Smart algorithms such as wakeword detection, tempo detection, song recognition, and many others have become an integral component of countless applications. These algorithms rely on a wide range of machine learning and/or traditional DSP techniques. While machine learning techniques are now solving previously impossible problems, algorithms designed with more traditional engineering techniques often require fewer system resources and are easier to deploy. In this talk we'll compare and contrast machine learning and traditional engineering approaches, and discuss fundamental principles that will help you determine what mix of techniques is best for your application.
Slides: https://data.audio.dev/talks/ADCxSF/designing-smart-algorithms/slides.pdf
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Amit Shoham
Amit Shoham has led dual careers as a musician and engineer. His professional roles have included DSP engineer, house music producer, DJ, computer vision engineer, remixer, deep learning engineer, mastering engineer, and troublemaker. Amit is currently a senior systems architect and algorithms guru at Artiphon, where his deep expertise in algorithm design and optimization helps bring to life innovative new musical instruments.
Streamed & Edited by Digital Medium Ltd - online.digital-medium.co.uk
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Organized and produced by JUCE: https://juce.com/
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Special thanks to the ADC22 Team:
Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
#audiodevcon #audiodev #deeplearning
