Master DSP with Eric Tarr: a professor in Audio Engineering Technology!

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Introduction

Eric Tarr is a professor at the Belmont University where he teaches Audio Signal Processing. In the audio programming community, he’s most famous for his book “Hack Audio” on the basics of digital signal processing using Matlab and his point-to-point modeling library for analog audio circuit emulation.

Eric’s work has definitely been an inspiration for starting the WolfSound blog and the YouTube channel so it’s really exciting to have him on the show!

In the podcast, we’ll delve into his story, how he learned audio signal processing, how he managed to work with some amazing audio companies (Sennheiser, Epic Games, Skywalker Sounds), and top tips on how to learn DSP coming from Eric’s teaching experience. We also discuss in detail how to model analog audio circuits for audio plugins (so called virtual analog modeling). Here, Eric describes which state-of-the-art methods are available and how you can learn them. He also shares the details of this point-to-point modeling library which allows you to easily emulate analog audio circuits.

As a special feat, I’d asked my coachees who follow Eric’s work to provide questions to him concerning a variety of different topics, including the impact of AI on the virtual analog modeling space.

All in all, it’s an episode that you don’t want to miss!

Note: If you like the podcast so far, please, go to Apple Podcasts and leave me a review there. You can do so on Spotify as well. It will benefit both sides: more reviews mean a broader reach on Apple Podcasts and feedback can help me to improve the show and provide better quality content to you. You can also subscribe and give a like on YouTube. Thank you for doing this 🙏

Episode contents

In this podcast episode, you will learn:

  • how Eric learned digital audio signal processing based on his passion for music and electronics,
  • how he became a professor for Audio Engineering Technology at the Belmont University,
  • how he wrote the famous “Hack Audio” book,
  • why he uses Matlab instead of Python in his teaching,
  • how he was able to deliver numerous audio-related projects to various companies worldwide,
  • how he developed his point-to-point audio circuit modeling library,
  • how you can learn digital signal processing (even if you’re just starting out),
  • what is the go-to language and technology stack for creating commercial audio products,
  • what are the state-of-the-art methods to model analog audio circuits,
  • is it worth going to the Audio Developer Conference?

This episode was recorded on January 19, 2024.

Tips from Eric on learning DSP

  1. You need to do some programming & maths to understand DSP.
  2. Use DSP for problem solving & troubleshooting to get familiar with the methodology and the terminology. Learn how to overcome obstacles and where to find solutions.
  3. Learning more maths and more programming always helps.
  4. Math basics you need to know for DSP
    1. Linear algebra
    2. Calculus
    3. Differential equations
  5. Programming basics you need to know for DSP
    1. Matlab or Python
    2. C++
  6. Necessary basics for audio circuit modeling:
    1. Ohm’s law
    2. Kirchhoff’s voltage laws (KVL)
    3. Kirchhoff’s current laws (KCL)
  7. How to evaluate circuit models?
    1. objectively with measurements
    2. subjectively with listening tests
  8. Analog circuit models don’t have to be 100% accurate, we should also strive toward “cool-sounding” circuits.
  9. C++ is the language to learn if you want to work in the audio industry; it’s the language of commercial products.

References

Below you’ll find all people, places, and references mentioned in the podcast episode.

  1. Eric Tarr
    1. Hack Audio: his personal website including online courses
    2. PhD
    3. university profile
    4. Hack Audio book
      1. Book’s source code in Python
    5. X @hackaudio
    6. Point-to-point audio circuit modeling library
      1. Eric’s talk about the library at the ADC22
      2. Matlab version
      3. Python version upcoming
      4. C++ library
        1. lite
        2. commercial
      5. Plugin presented at ADC23: upcoming
      6. ADC workshop on the library: not available to the general public
  2. Universities & Companies
    1. Belmont University
      1. Undergraduate audio engineering technology program
      2. Master’s program in audio engineering
    2. Ohio State University
    3. Capital University
    4. Celemony Melodyne
    5. Skywalker Sound
    6. Sennheiser
  3. Resources on digital audio signal processing & audio programming recommended by Eric
    1. Audio Developer Conference
    2. The Audio Programmer YouTube channel by Joshua Hodge
    3. Online books by Julius O. Smith III
    4. The Acoustical Society of America
    5. Audio Engineering Society (AES)
      1. AES Journal
      2. Conferences (and their proceedings, i.e., articles submitted)
    6. DAFX conference (and its proceedings, i.e., articles submitted)
      1. DAFX paper on model bending
  4. Programming languages
    1. Python
    2. C++
      1. JUCE C++ framework
    3. Matlab
    4. LaTeX typesetting language
  5. Audio effects
    1. chorus
    2. flanger
    3. compressor
    4. wah-wah
    5. algorithmic reverb
    6. analog modeling
  6. Circuit analysis methods
    1. Nodal analysis (NA)
    2. Modified nodal analysis (MNA)
    3. State-Space Analysis (SSA)
    4. DK method
    5. AI
    6. Deep learning
    7. Black-box vs white-box approach
  7. Popular analog audio devices
    1. Fender Bassman
    2. Ibanez Tubescream pedal
    3. 12AX7 triode (paper recommended by Eric that models it)

Thank you for listening! 🙏

Who should I invite next? Let me know in the comments below!