Apply neural networks to Virtual Analog modeling of audio effects.
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In this podcast episode, I was lucky to interview another member of the Aalto Acoustics Lab of the Aalto University in Espoo, Finland. He is involved in research applying deep learning to audio, for example, in the context of Virtual Analog modeling of guitar amplifiers. He was also the advisor of my Master Thesis.
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Episode Contents
In this podcast episode, you will learn
- how to transition from mechanical engineering to audio processing,
- how to apply deep learning to music processing, for example, virtual analog modeling,
- challenges of deep learning in audio,
- how to use neural networks in real-time audio,
- what makes a good audio dataset,
- how to fuse traditional DSP and deep learning,
- typical neural network architectures in audio,
- generative models in audio,
- how transition from the Master’s to the PhD mindset,
- challenges of remote research collaboration during pandemic,
- transition from Scotland to Finland.
Referenced Resources
Below are all the resources that are referenced in the podcast episode.
- People
- Alec Wright, a doctoral candidate at the Aalto Acoustics Lab
- Vesa Välimäki, head of the Audio Signal Processing group at the Aalto Acoustics Lab.
- Stefan Bilbao, head of the Acoustics and Audio Group at the University of Edinburgh
- Places
- Acoustics and Music Technology master’s degree at the University of Edinburgh
- Aalto Acoustics Lab of the Aalto University in Espoo, Finland
- Deep learning research
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