A Review of Deep Learning Architectures

Deep Learning is a vast field within computer science that has made tremendous progress in its application and abilities in the past decade. Some applications of deep learning include image recognition, language translation, neural audio effects, self-driving automobiles, and even cancer diagnosis. In this paper, we will explore some foundational architectures of deep learning as well as their various applications. We will then go on to discuss our hands-on experience with transfer learning using ResNet, an architecture for the task of image classification.

Introduction to Digital Signal Processing (DSP)

A few years ago, I expressed my interest in learning DSP to a professor of mine. He recommended that I check out the book 'Designing Audio Effect Plugins in C++ with DSP Theory' (2013) by Will C. Pirkle (ISBN: 978-1-138-59189-9). This blog post is completely for academic purposes. The book is amazing and I highly recommend it for those looking to get into the world of audio effects plug-ins and digital (audio) signal processing. In these blog posts I will be sharing my notes from the book.

Anatomy of an Audio Effect Plugin

In this post, I will be diving into the separate components that make up the anatomy of an audio plugin. This information was gathered from the book Designing Audio Effect Plugins in C++ For AAX, AU, and VST3 with DSP Theory by Will C. Pirkle (ISBN 13: 978-1138591936). Using this information, as well as Will's Youtube videos, I was able to create a basic volume plugin. The source code for that plugin can be found on my Github repo: Hello Volume. See the README.md file for the links to Will's videos on Youtube in case you're interested in creating your own plugin from scratch as I have done here. Below you'll find my notes from Chapter 2 - Anatomy of an Audio Plugin from Will's book. I hope you enjoy!

How DSP Filters Work

In this post I will be diving into how DSP filters work. We will cover fundamental concepts such as frequency and phase response plots. Once we have this ground-work laid we will implement our knowledge by studying First Order Feed-Forward and First Order Feed-Back Filters.

A Review of Automata Theory

Coming soon!

Generative Music AI

Coming soon!