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Ready for takeoff.
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Well, welcome to RubyConf! I'm really happy to be here.
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It's nice to be in person. Today, I'm going to talk about music, specifically recorded music.
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I'll discuss the kinds of tricks that producers and musicians use to make the sound good, and I'll explain that with some Ruby code.
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What I like to do is use programming to understand the world. The world is a very complicated place, and as programmers, we have this amazing tool to actually comprehend things.
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When you write code, you have to understand it; otherwise, you can't write it. This compels you to learn it, and that's what I did with music.
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So today, I want to take you through a process where you don't just understand it but also try to write some code.
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After a while, you start to grasp it, and you end up with hopefully some simple code and examples that I'll share with you.
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Let’s begin with a very brief history of the technology behind music that has developed over the last several years, which will lead us to digital audio.
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This is where we can start using Ruby to actually see what's going on.
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There are several code examples accompanying this talk. You can find those here, and I will also post the slides after the talk.
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If you want to follow along, you can quickly go to this link.
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So, what is music? It is described by a few key aspects.
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Audio, like what you are hearing right now, is a waveform moving through the air. Air molecules bounce against each other, and our ears perceive these vibrations.
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The easiest way to visualize this is to compare it to waves in a pool of water, but instead of water molecules, we have air molecules.
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These waves travel through the air from a sound source to your ears, where tiny hair cells called follicles vibrate in response to these sound waves.
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Your brain then processes this signal to create the illusion of speech or music. So, there isn't anything inherently musical about these physical phenomena.
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Your brain generates models to make sense of the incoming vibrations. Neuroscientists don't fully understand how this works yet, so there is a bit of magic involved.
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Let’s explore the basic patterns that the brain uses to map these sounds.
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The first important concept is pitch.
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Pitch refers to the frequency of oscillations per second. A lower pitch corresponds to fewer oscillations, while a higher pitch corresponds to more.
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For example, a bass guitar produces lower pitches, while a violin produces higher pitches.
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Let’s listen to a basic pitch that sounds like this.
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[Pitch Example]
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We're all familiar with that sound.
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The next element is timbre, which refers to the unique quality or color of a sound.
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Timbre encompasses all the variations within pitches.
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An example of timbre can be heard in a classic Beatles song from the 1960s, where different instruments contribute to the overall depth of the sound.
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Finally, we have tempo, which is established through the presence of silence between sound waves.
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This silence contributes to the perception of rhythm and can create a loop.
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If we combine pitch, timbre, and tempo, we create a musical piece that sounds something like this.
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Historically, music was always live; there was no recorded music until technology evolved.
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This technological advancement changed the world in many ways, leading to the advent of recorded music.
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Let’s quickly review the steps that led us to digital audio.
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It all started with Thomas Edison, who developed a device that could etch sound onto a wax cylinder using vibrations from sound.
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However, due to Edison's patent, this technology did not gain traction.
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A different inventor, Berliner, proposed using discs instead of cylinders, which became the dominant format for recorded music.
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After discovering magnetic tape technology, audio recording quality significantly improved, which facilitated multi-channel recording and transformed the music industry.
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In the 1980s, music became digital, marking a shift from analog grooves to CDs and modern computer technology.
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Now, we can use software to replicate tools that were once available only in large studios, making powerful audio production accessible.
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Next, we’ll dive into what digital audio actually is and replicate some popular tools using Ruby to better grasp their functions.
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Digital audio consists of samples; when we take a waveform, we can measure the intensity of the signal at specific points.
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By using these samples, we can recreate and play back the sound.
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Often, we process this data as a sequence of numbers, which allows for manipulation and playback.
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In this presentation, I’ve chosen the wave file gem, a Ruby library for reading and writing WAVE files.
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This gem enables us to read a WAVE file into a large array of samples, simplifying audio processing.
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Let’s visualize this with an audio sample.
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[Sample Visualization] Now that we have a representation of our audio data, we can start using some Ruby functions to analyze and modify these samples.
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In fact, our first step will be to amplify the audio using Ruby.
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By multiplying each sample by a factor, we can increase their amplitude and create a higher volume.
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Let’s try this with a sound sample and listen to how the amplification affects the sound.
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[Amplification Example] You can hear the increased volume, represented by peaks that rise higher than before.
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However, if we amplify too much, we risk clipping, which distorts the sound and is generally undesirable.
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Clipping occurs when the peaks exceed the limits of the waveform, leading to a harsh distortion.
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Let’s listen to how clipping sounds.
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[Clipping Example] This distortion is often used in genres like heavy metal to achieve a specific sound quality.
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Next up, we’ll discuss mixing. Mixing involves merging audio tracks together to create more complex soundscapes.
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When mixing, we can take several audio samples and sum them up to produce a new waveform that combines elements from each sample.
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Let’s see how this works when we mix two audio samples.
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[Mixing Example] You can hear how the combination of sounds builds a richer auditory experience.
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Following mixing, we will cover compression, a technique used by audio engineers to enhance the overall loudness of a sound.
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Compression targets the peaks of sounds to bring them down, which allows for an overall louder mix without distortion.
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In radio or popular music, compression is employed extensively. Let’s see how we can achieve compression using Ruby.
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The process involves defining a threshold that determines when a signal is too loud, and reducing the volume of those peaks.
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After lowering the peaks, we can apply a makeup gain to raise the overall volumes while avoiding clipping.
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Let’s listen to an example of this compression process.
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[Compression Example] You can notice the difference in how much more balanced this sound is compared to the uncompressed version...
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Now, let’s switch gears to sound synthesis. Many contemporary music pieces use synthesizers to generate sounds.
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For example, we’ll start with generating noise through Ruby, which we can do using random number functions.
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The output will appear chaotic, representing the randomness associated with noise.
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Let’s visualize this noise sample.
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[Noise Sample Visualization] You'll see how noise can form the basis of percussive sounds in electronic music.
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Next, we’ll explore square waves, which represent the simplest oscillating sound.
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Let’s create a square wave using Ruby and listen to its output.
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[Square Wave Example] Although it produces a 'blunt' sound, it’s a fundamental element within electronic compositions.
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Now, we’ll delve into sine waves, the core building blocks of many sounds.
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Generating a sine wave involves using a mathematical function to plot samples in a circular motion.
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Let’s visualize and listen to what a sine wave sounds like.
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[Sine Wave Example] This smooth waveform is commonly used across various music genres.
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Building on that, we can combine multiple oscillators at different frequencies to create chords.
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Mixing these oscillators produces complex harmonic sounds that lend richness to our music.
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Let’s hear how this combination sounds.
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[Chord Example] This is how we can produce rich harmonic textures in our compositions.
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If you’re interested in further exploration, I encourage you to look into Fourier transforms, where you can deconstruct complex sounds into their sine wave components.
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This is valuable for recognizing patterns in sound and has applications in graph theory and data analysis.
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Finally, let’s talk about creating tambre through the combination of different waveforms.
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By mixing sine waves and square waves, we can generate unique wave shapes that sound richer and fuller.
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Let’s listen to this final sound example that illustrates this mixture.
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[Final Hybrid Wave Example] It’s fascinating how from simple building blocks, we can create intricate musical landscapes.
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That brings us to the end of my presentation.
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I appreciate your engagement and enthusiasm for this exploration of how music works.
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As a fun note, I’ve even created a cover of my favorite song using only the samples generated here today.
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[Musical Outro]
