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More “Upbeat” Musical Examples

Since Fresh Minds Season 4 has a lot of pieces that focus on immersive and persistent textures and slow progressions, here are some finalists from previous seasons that use more active and expressive foreground elements with more traditional phrasing for contrast. You might find these to be helpful references as you’re working on your own composition project.

 

Notes on the Golden Ratio

In today’s MUSC 316 class, Sam and Randall presented their analyses of Joo Won Park’s Elegy. They varied in significant ways but weren’t incompatible. I want to use this opportunity to show how a mathematical model found frequently in nature illuminates and connects points Sam and Randall made today.

I may have mentioned the Golden Ratio in this class briefly when we were discussing form. If you dig maths but haven’t heard of this before: sorry, there goes your evening, along with some of your friends if you can’t stop talking about it. If you need to create a final composition project with a fixed length and have no idea for a formal structure: you’re welcome.

What It Is

You might have heard of the Rule of Thirds in visual arts, the notion that images seem to be more interesting when key foreground objects and backgrounds (like the horizon or treeline) coincide with lines dividing the image into a 3×3 grid. In nature, mathematicians have found that divisions at 62% are more natural and common than 50% or 2/3, but 62% is close to 2/3. This may explain why the Rule of Thirds is readily taken with some liberties leaning toward the center.

Here is an article by Icon Photography School with examples of the Golden Ratio in imagery, including a video by DNews which is also helpful: https://photographyicon.com/goldenratio/

In Music

Anyway, it works in time-based works as well, and Park’s Elegy is a great example. The golden ratio point (about 62% from the beginning) is about 2’ 44”, where Sam heard the “balloon of serenity” burst and return to “rough” pitch clusters; Randall described this point as being where the only sustained single pitch ends and the two-pitch clusters return. If you’re keeping track of exact pitches, you’d notice that this returning cluster is the same as the opening and closing motive, just up an octave (D–E-flat), and the melodica simply ruminates on that dyad for the rest of the piece (motivic development has concluded and waits for the other parameters to reach their closure—parameters like pitch range, loudness, and visual clarity/blur). This 62% point is a common place to find climaxes, recapitulations, or other significant moments.

It is sometimes useful to look at 62% from the ending as well, in this case about 1’ 38”. It’s around that point that Sam noted a distinct change in attitude and Randall noted that the two-pitch clash returns after the motives have change from ascending to descending. If you were keeping track of pitches, you would further notice that the music had only used a C Dorian scale so far (C minor, except with A-natural instead of A-flat). The first descending motive introduces an A-flat, which, you might argue, opens a middle section that disrupts what had been established in the opening. That A-flat “disruption” is set aright in the accompaniment with an A-natural that happens to be right about the 50% point in the piece. 50% divisions are uncommon and rarely effective, but its precision makes me wonder if it was an intentional design.

Visually, the double image fades in leading up to this point and moves around the most turbulently after the descending clash. The video returns to the single image as the melodica plays the single sustained C.

These divisions portion the piece nicely into three sections (and I can see them being divided into smaller sections too, so Randall’s slightly different 3-section model and Sam’s 5-section model are still valid): I see an opening in which a rough clashing half-step pitch cluster expands into wider, more consonant intervals (divided into ascending and descending halves, as Randall noted), a middle section that goes back to the half-step cluster and reaches its widest point at the 50% mark and then settles on a single sustained pitch (which happens to be C) (which could be two distinct smaller sections, as Sam saw it), and a closing section that ruminates on the opening D-E-flat half step cluster. You also might find that this closing section consists of four motives in the melodica: 1. the opening dyad an octave higher, 2. the opening of the middle section but upside down (descending turned into ascending, and still echoing the D–E-flat dyad), 3. a sustained C (like the end of the middle section) but thwarted at the end by becoming an ascending cluster (the first descending motive backwards?), and 4. the opening motive repeated, more closely, as Randall noted.

Golden Subdivisions

Taking my first section alone, the Golden Ratio point is at 1:00 where both students show the change from ascending to descending motives. Taking the last section alone, the Golden Ratio point is where the last melodica motive enters, where Randall notes the return of the opening motive and Sam notes arrival at acceptance.

So What’s the Right Answer?

This is a great example of what I mean when I say, “There are few wrong answers; mostly poorly-supported answers.” Sam and Randall presented valid and supported models that were different in significant ways. They each work well, and they each highlight different aspects of the work. Their differences don’t make them wrong; their consideredness and supporting points make them each strong.

NOTE 1: DON’T take the Golden Ratio as an absolute rule or requirement! However, do feel free to use it as an often-effective rule of thumb whenever you can’t make up your mind on the proportions among things.

NOTE 2: Yes, I did mention pitch here, because it’s important to certain readings of the piece. Notice that Sam and Randall got there quite well without referring to pitch. Talking about pitch is not off limits when it’s playing a significant role. If you were focused too much on pitch, you might get stuck on the C minor (C Dorian) modality of the piece, which isn’t a dynamic element—it’s just wallpaper, and you might miss many significant points instead. For your analysis, talk about whatever you find contributes to a model that explains how most elements within the piece work together. For your composition project, be careful that it relies on course concepts for its substance, not relying on melody, key/modality, or constant metric structure for its substance.

A couple other observations:

  • Those wind and wave sounds are surprisingly harsh, but they’re kept at a striking “distance” from us. It’s not a dynamic element in the piece, but it does help set the stage for the thoughts that occurred to us during the piece by separating our emotions from physical presence so starkly.
  • As I said in class, this is a good example of the subtle detail required to make a “one concept / one moment” piece successful. We might describe it as “just sad melodica sighs and waves…,” but if it didn’t have all these other details we noticed, then we would follow our statement with “…and it was dumb/worthless” instead of being able to appreciate its well-crafted focus. Keep this in mind as you conceive your final compositions: it takes many subtle details to make “simplicity” not “suck” (so to say).

Publishing Your Composition and Slideshow Documentation

The final destination for your composition project and documentation is a publicly published video slideshow, playing your composition in full, with onscreen annotations highlighting the pertinent points of your documentation, along with your full prose documentation included in the notes on the video page. YouTube is recommended; other sites like Vimeo may also be acceptable, but get approval from your instructor in advance before using a different service. Also consult your instructor in advance if you are uncomfortable making your project fully public. Continue reading

Analysis Notes

1. These aren’t songs

Songs are specific forms of music that are sung or have a singable tune. You might describe moments or elements in your assigned composition as “song-like,” but you will have a hard time justifying calling them songs outright. Instead, try using one of the following ways to refer to the work:

  • “composition”
  • “piece”
  • “work”
  • “movement” in the case of a multi-movement piece like Sud
  • simply by the title of the  composition

Songs aren’t bad things, but these compositions aren’t songs. Refer to the songs & sandwiches discussion in class.

2. Avoid asserting how a sound was made

While it’s a great exercise to guess how you might go about making the sounds you hear, and it’s a worthy endeavor in some other class to figure out how a composer achieved specific sounds, those aren’t the point of this project, so avoid doing it even by accident. You most likely don’t know for sure how the composer made the sounds you hear, so avoid terms that suggest that you do, like “random” (try busy, hectic, complex, complicated, sporadic) or “synthesized” (try synthetic or synthetic-sounding).

3. A play-by-play is not an analysis

…although it is often the first step toward one. Think of a football game. Don’t tell me what happened each down when I ask what the game was like.  Tell me what happened in the game that made it exciting and different from other games. You do need to think about everything that happens in your composition before you can say anything meaningful about it as a whole, but a play-by-play does not make an analysis of how the piece works as a whole.

more Analysis Advice

1. Don’t tell me you like it

Because (for the purposes of this course) I don’t care. The purpose of the analysis isn’t to prove to me that you like this stuff now. It’s difficult listening, and it was chosen for a pedagogical purpose (refer to discussions on the first day). Your analysis should show the reader how the piece works, how to make sense of it, get something meaningful from it.

2. “No wrong answers” doesn’t mean everything is right.

I’ve said before that in this project, there are few wrong answers, but many unsupported ones. It’s okay if this makes you uneasy, because it may be new for you. However, don’t let yourself think that means your work won’t be evaluated seriously. In recent teaching workshops, I’ve been shown research on different stages of learning that all basically boil down to four stages:

  1. Teacher is right—trust an authority figure absolutely. But eventually you’ll come across a teacher who is wrong, and your world is shattered.
  2. Procedure is right—the ability to determine right from wrong is in your hands (e.g., If ____ and ____ then definitely _____), but procedures can’t universally fit all cases, and procedures can be improperly applied (e.g., this dog only has two legs, therefore dogs are bipeds).
  3. Everything is right (in its own special way, la la la la)—also called relativism. It recognizes that there can me many right answers, but shies away from admitting that things can still be wrong.
  4. Constructed knowledge—at this stage, you recognize that there can be many valid answers, that some may be generated by procedures or consulting experts, but you also recognize that any of those things can also be wrong or at least used improperly. With this knowledge, you take in theses and evidence, evaluate them in context and form your own informed answer.

So, if our approach to evaluating analyses in class has been uncomfortable for you. Be heartened—you’re growing!

3. Narratives are natural (but not always sufficient)

If you catch yourself thinking, “This sounds like an alien invasion; the aliens are attacked with cannons, and… eventually one side wins,” that’s okay as a start—it’s very natural to use narratives (stories) to make sense of things. E.M. Forster reflected on this in Howard’s End:

“It will be generally admitted that Beethoven’s Fifth Symphony is the most sublime noise that has ever penetrated into the ear of man. All sorts and conditions are satisfied by it. Whether you are like Mrs. Munt, and tap surreptitiously when the tunes come– of course, not so as to disturb the others–or like Helen, who can see heroes and shipwrecks in the music’s flood; or like Margaret, who can only see the music; or like Tibby, who is profoundly versed in counterpoint, and holds the full score open on his knee…”‘

So, don’t be afraid of using narratives, but heed these warnings:

  • Remember that models/narratives/metaphors always fail us at some point. The show us certain things about a subject, but not every conclusion made from the narrative will be true for the subject (e.g., Africa doesn’t really have a stain where you dripped coffee on your map). Find the right scale, context, and limits of your narrative’s applicability. In most cases, your narrative will best serve you as a parallel path to discovering a way to describe the interrelationships you see, in more abstract terms.
  • Sticking with a narrative means you’ll probably need to spend most of your essay connecting sonic elements and events with characters and events in your narrative, which brings you dangerously close to giving a play-by-play account without any larger view of the whole. Always make sure you’re connecting your conclusions back to the sounds in the music and to the big picture.
  • Don’t force a narrative on the piece. It just might not fit, or in might only be helpful to a certain level of detail. Once you find a narrative that fits in certain ways, it’s great if you look closer and find sonic details that fit details of your narrative, but if it doesn’t fit, don’t force it.
  • Back to the example at the start of this section: if you use a narrative, check to see what that narrative may reveal about you. If you say, “This sounds like an alien invasion…,” what is it that makes it sound alien? Is it just because you’ve never heard anything like it before? It’s probably not a useful analysis if you’re only comparing it to your own life experience or subjective tastes. Why an invasion? It’s not just because this unfamiliar (to you) is simply persisting in its presence, its own right to exist, is it? Be very careful when using terms that suggest value statements, intentions, or motivations like this: Find the underlying reasoning leading to these conclusions, and if you find they have emerged from your own bias, discard them. They’re preventing you from finding an objective model to understand the work.

 

The Football Analogy

1. Someone’s trying to tell you something

When approaching unfamiliar art, my best advice to an audience is to imagine that it’s a message from an alien: you know someone is trying to tell you something, and you know your usual tricks for making sense of it may not be helpful.

2. Stick with it

The longer version of this considers the alternative. Imagine an alien were watching a game of football. He might be inclined to say “it’s just a bunch of humans running all over,” and ignore it. He’d be missing a lot of understanding about humans and maybe missing out on an enjoyable experience. If the alien decided to stick with it longer, he might notice that certain things are predictable, other things are not predictable, and that sometimes would-be predictable moments have thrilling surprises.

(This concept is adapted from Richard Taruskin’s evocations of a “Martian musicologist,” speculating on what would appear to be most important in our music, from the perspective of an extreme outsider to our culture. Richard Taruskin, “Reply to van den Toorn,” In Theory Only 10, no. 3 [October 1987].)

3. Where’s the playing field? Who are they players? Where are their goals? (How) do they get there?

The alien might notice things gradually about the football game, and gradually begin to make sense of it, then compare it to other football games, and maybe enjoy it. These are some gradual realizations the alien might have.

  1. It’s just a bunch of humans running all over.
  2. Well, they run around inside this green rectangle.
  3. Actually, half of the people run in one direction, and half face the other way.
  4. Oh, there’s a ball, too.
  5. They all seem to be following the ball around, with half of them moving the ball, and the others trying to stop it.
  6. The people stop running when one person moves the ball to one end of the green rectangle.
  7. They actually run and then stop, then start again.
  8. They usually do that four times, and if the ball hasn’t reached the end yet, the other people try to move it to the opposite end.

and so on.

Try this process when you encounter new art. You might not find meaning in the usual places. If you’re used to listening to melodies and beats, but a piece has a constant pitch and a steady pulse with no pattern to it, then there’s no meaning there: that’s just the playing field. Instead, listen for meaningful patterns and developments in timbre or loudness or space (e.g., left/right): they may be the players. Next, figure out their goals, how they try to get there, whether they ever get there, etc.

For further reading on this approach, look at Richard Schechner’s “Seven Ways to Approach Play” from Performance Studies: An Introduction (Routledge) on eCampus.

Graphic Score Notes

1. You can’t show it all

…so figure out what’s most important and find a way to demonstrate that. It will be different for every piece. DO NOT give a play-by-play account in your analysis. The inventory of events that happen is one step on the way to understanding how the piece works, but in itself, it is not an analysis.

2. Mixed approaches to notation

Stockhausen, Study II (1954) was completely scientific in its approach, but you miss the musical relationships.

Stockhausen, Kontakte (1960; excerpt) uses a combination of multiple staves, shapes suggestive of scientific parameters, shapes suggestive of traditional music notation, and plain words (which are in his native language, German):

Luening/Ussachevsky, Incantation (1953) was an early composition made by editing sounds recorded on tape. Modern scholar Brian Evans made a graphic score of it using only a few symbols, and marking its sections. He clearly didn’t notate every single sound.

3. Relationships, not just a list of sounds

Harvey, Mortuos Plango, Vivos Voco (1980) only has two sound sources in it, so Dr. Evans had to focus on how the sounds were transformed, more than an inventory of which sound happened when.


See more examples and discussion on graphic scores here.

Processing Notes

How to make sense of almost any effects processor: Know the basic types and find the bare bones parameters.

Controls that most processes will have:
  • Bypass. This switch lets the original signal through so you can quickly compare the processed version to the original.
  • Wet/dry mix. “Wet” means the processed signal; “dry” means the unprocessed original signal.
  • Presets. Factory-suggested settings offer good starting points, but if you always rely on presets without tweaking them at all, then you’re not going to have an original sound and you might not really understand what the process is actually doing to your sound.
  • Output gain. Some processes make a sound a lot louder or quieter as a side effect. This control allows you to adjust for that and keep your sound at a usable loudness.
  • Input gain: Some processes have different results when they operate on a loud sound or a quiet sound. This lets you “tune” your input to get the desired response from the process. You’ll probably need to adjust the Output Gain in the opposite direction.
Time Domain processes manipulate the sound by working only with what we see in a waveform view: amplitude changing over time. Not surprisingly, many time domain process with affect the amplitude or the time of a sound. However, with some cleverness, the spectrum of a sound can be affected, too. The most commonly known and used processes are time domain processes.
Delays simply copy a sound and play it again later. You can get a wide variety of effects from it, though, if you’re clever.
  • Delay period or time. This is how much you want to delay a sound in seconds or milliseconds. From 0–30ms, we don’t hear separate copies of a sound, just slightly different (usually anemic) timbres, due to phase cancellation. Up to 100ms, a sound might sound thicker or “doubled.” Over 100ms, the delayed sound will start to sound separate from the original. Natural acoustic echoes are usually 100–500ms. Anything longer starts to sound like a “call and response” echo of a second musical voice.
  • Feedback. One delayed copy can be nice, but if you feed the output of the delay process back into its own input, you get an endless stream of delayed copies (e.g., “HELLO-ELLO-Ello-ello…”). The feedback control determines how much of the original sound to let back in (i.e., how loud). It’s usually shown as a percentage, but sometimes appears in decibels. One-hundred precent or 0dB means the full output is copied (and will never die away). You can make a looper with a delay time of a few seconds or more with a feedback at or just below 100%.
  • Special trick: Comb Filters. We mentioned phase cancellation with short delay periods. Add some very high feedback (almost but not quite 100%), and several frequencies will be cut out and others will resonate, leaving a metallic, ringing harmonic series with its fundamental frequency based on the delay period. The resulting spectrum looks like a comb. Now you can start to see how we can get other effects like reverbs and filters by starting with a simple time-domain delay.
Reverberation is basically an infinite mass of delays bouncing all around a room. It is often used to suggest physical surroundings and distance of a sound, to smooth out roughness in a sound (like a timid shaky vocalist), or fill silences to keep a mix from feeling too sparse.
  • Decay time dictates how long it takes for a sound to die away (a fall of 60dB is a standard point to measure). Longer decay times suggest more reflective surfaces in a space.
  • Pre-delay or early reflections. In natural reverberation, you will hear a few very quick “slap” echoes (from nearby surfaces) before the smooth rush of reverberation arrives. You might be able to set the pre-delay, the time before the smooth reverberation comes in. Longer pre-delay suggests larger rooms. Alternatively, you might be offered a control for the duration or loudness of early reflections.
  • Diffusion. Since reverb is just a mess of individual echoes, a room with a few flat surfaces may have a “lumpier” reverb and a room with many irregular surfaces may have a “smoother” reverb. Diffusion makes it smoother.
  • Damping. It’s natural for walls, floors, etc. to absorb high frequencies faster than low frequencies, so it’s common to simulate this with a filter that reduces high frequencies (see filters below). More damping suggests more absorbent materials in a room (like carpet or people).

Dynamics effects change the loudness of a sound, or change based on the loudness of their input. The two basic types are gates and limiters. An expander is a more forgiving form of gate, and a compressor is a more forgiving form of limiter. These are often used for as utilities, e.g., to fix problems.

  • Threshold. This is the loudness above/below which the process jumps into action. A gate will silence any sound when it falls below the threshold; this is useful for cutting out unwanted background noise or tightening up sloppy attacks or releases. A limiter will try to turn down a sound once its loudness reaches a threshold in order to keep it from getting any louder; this is useful for adding sustain (by smashing the attack), keeping a signal from clipping (going over 0dB and getting cut off more harshly), or keeping a voice in the foreground (by reducing the dynamic range and making it all louder with output gain).
  • AttackRelease, and Hold. These control how quickly the processes take effect and go back to normal. Hold allows you to avoid overly fidgety effects by making it stay active for a certain amount of time before it can change back.
  • Ratio. Gates and limiters are not forgiving: all the sound or none (gates) or nothing any louder than the given threshold (limiters). This is all-or-nothing with no grey in the middle. An compressor is like a limiter, but it allows some grey area above the threshold by attenuating (reducing the loudness) of sound gradually. A 2:1 compression ratio means for any sound louder than the threshold, it attenuates it to bring it halfway back to the threshold; a 10:1 compression ratio is more extreme; a limiter is basically a compressor with a very very high ratio. Conversely, an expander is a gate with some grey area: an expansion ratio of 1:2 means that instead of silencing a sound below the threshold, it just cuts the volume in half.
  • Key or Sidechain. This is really cool. You can often make dynamics processes listen to a different sound from the one they’re actually processing. If your bassist has sloppy attacks but your bass drum is solid, put a gate on the bass and set the key or sidechain to listen to the drum; the gate will use the bass drum’s sound to shape the bass guitar’s sound—this is a great way to “carve” rhythms out of sustained sounds, too. A ducker is just a compressor with a sidechain: automate balance between lead guitar and vocalist by putting a compressor on the guitar with a sidechain listening to the vocal. When the vocalist enters, the compressor  will make the guitar quieter and let it return to full volume when the vocalist takes a breath between phrases.
  • Knee. Well, when you graph out input loudness versus output loudness, there’s always going to be a bend at the threshold that looks like a knee. You usually get to pick between a “hard” and “soft” knee, with a soft knee fudging the behavior around the threshold a bit to avoid suddenly starting or stopping changes in volume.
Filters/Equalizers (EQ) shape the spectrum of a sound by emphasizing or deemphasizing certain frequency bands. Think of a running average: it sums and divides the last few numbers (samples) in order to smooth out any abrupt changes (i.e., reduce high frequencies). Filters can be used to reduce unwanted noise, help different sounds blend together, or adjust their character by emphasizing different frequency ranges.
  • Filter type: what range of frequencies will it affect, and what will it do? High-passlow-pass, and band-pass filters leave a certain range of frequencies (called a band) unchanged, and they eliminate everything else. High shelvinglow shelving, and peak/notch filters boost or reduce a range of frequencies and leave others unchanged.
  • Cutoff or center frequency: set the upper/lower limit or center of the frequencies affected.
  • Qbandwidth, sloperoll-off, or resonance: Think of a band-pass filter. You might know the center frequency, but you don’t yet know what range of frequencies above and below the center to pass. There are side effects to using time domain processes to affect frequency, though: there’s a gradual transition between the affected frequencies and the others. The slope or roll-off might let you control the steepness of the filter directly. A narrower bandwidth is going to have a steeper slope. The Q (quality) factor is the inverse of bandwidth (1/x), so high Q means a narrow bandwidth. Finally, with some filter formulas will cause a sound to resonate or ringing sound at the cutoff/center frequency. High Q or steep slope will result in greater resonance.
Other common time domain processes you may see:
  • Distortion, overdrive, fuzz, amp modeler, saturation. These all chop off the tops of your waveforms in natural, gritty, lovable ways that physical objects like guitar amplifiers or analog magnetic tape do. That is, they leave rough edges instead of harshly chopping of the peaks. That results in a less harsh sound with some interesting character, character that responds differently to loud and soft sounds, sounds with wide dynamic ranges or narrow ones. Sometimes you’re offered controls for an amount of overdrive (amplification) and a filter to reduce harsh high frequencies (as in nature). Other processes will let you pretend to choose guitar amp models, mic types, and mic positions.
  • Amplitude Modulation and Ring Modulation. Now this is interesting. It turns out that when you fade a sound in and out very fast (more than 20 times per second—sound familiar?) then it no longer sounds like changes in volume or pulsing rhythm. It changes the timbre in a surprising way. The original partials are canceled out replaced by two copies: one set higher than the original, and one set lower, like two frequency shifts (see below). But that’s just when you change the volume in a sine wave pattern. Ring modulation does more. Remember that changing volume is just multiplying: times zero = silence, time one = full volume. So, what I just described is like multiplying a sound by a single singe wave (called amplitude modulation). Ring modulation (named for the shape of the analog electrical circuit that does this) multiplies a signal by itself, creating a very rich and complicated web of inharmonic partials that all change in natural ways in response to the original sound. That said, it’s commonly used for aliens, robots, and radio signals with a lot of interference.
  • Flangerchorusphaser. No big whoop. See Modulation below.
  • Bit munging or degrading. It’s a digital signal, so why not mess directly with its digitalness? These processes will let you simulate lower sample rates (making muddier sounds and aliasing) or bit depths (resulting in harsh background noise). With extreme settings, it sounds like a cheap toy or losing at Space Invaders. Subtle amounts of aliasing, however, can add a delicate shimmer to a sound, and gradually reducing bit depth (especially with a reverb to smooth out sudden changes in bit depth) can make a sound “morph” into or out from pure noise.
Frequency Domain processes can see and manipulate the partials in a sound’s spectrum, because the sound as gone through a FFT (Fast Fourier Transform) to break the sound into sine waves with different frequencies and amplitudes. This is like boiling a sound down to its “recipe” (analysis)—then you can tweak that recipe and remake the sound differently (resynthesis). This allows for some very creative and unexpected results.
  • Time vs frequency, pitch versus rhythm, FFT sizewindow size, or frequency resolution. When you perform an FFT, you must have a tradeoff between time resolution and frequency resolution—one or the other must be blurred (much like Heisenberg’s Uncertainty Principle, if you know what that is). You might be asked to favor pitch accuracy or rhythmic accuracy, or you might be asked for a window size in samples (larger windows blur time more but allow more refined pitch processing) or frequency resolution (finer frequency resolution means more time blurring). Either your attacks or your timbre has to get fuzzy. That’s the trade-of for this kind of control over your sound, so use frequency domain effects strategically, or use them intentionally for the artifacts they produce. If you’re offered an overlap factor (meaning how many analysis windows overlap), you might be able to make up for some time blurring and get away with larger windows.
  • Time stretch or pitch shift/transpose. Once you have the recipe of the sound, it’s simple to make it all just slower or just higher without changing the other. Extreme time stretch values will make the windows audible: you’ll hear a stuttering or stair-stepped effect. Pitch shifters might allow for harmonic correction, meaning it will try to impose the original spectral envelope onto the new shifted partials in an attempt to avoid the “chipmunk” effect and offer a more realistic illusion of the original sound source simply singing higher.
  • Frequency shift is like pitch shifting with one critical difference: Whereas in pitch shifting you multiply all frequencies by a given number (e.g., doubling them=transposing up an octave), frequency shifting means adding the same value to every partial. This means the farther you frequency shift a harmonic series, the less it will be a harmonic series (integer multiples of the fundamental, or evenly spaced including 0Hz, e.g., 100, 200, 300… becomes 110, 210, 310…). This means it won’t sound as strongly pitched, and it will have strong inharmonic partials, making a sound more metallic or synthetic sounding.
  • Pitch correction. This is a flaky process with well-known artifacts. The software tries to detect harmonic series in a sound to determine what pitches are present, then round all partials in that series to the nearest pitch on a piano keyboard (the tuning system called 12-tone equal temperament). Software like this is often wrong or fidgety, resulting in quirky jumps (to be avoided or embraced strategically). Fully correcting pitches results in unnaturally static sounds (voices sound robotic instead of human), so there is often a control for how much to change a pitch (e.g., splitting the difference) or an acceptable margin before the process takes control.
  • Spectral filters have no slope (as time domain filters do), just razor-precision. They’re often not worth the artifacts unless that’s what you’re after.
  • Spectral gates can be refined noise reduction tools. They apply a loudness threshold (like time domain gates) to each frequency band separately, not the whole signal, so you can eliminate or reduce all the weak partials (which are likely to be unwanted noise). Higher thresholds reduce your sound to a kind of pointillistic “spectral splatter”—an interesting way to extract pitched motives from noisy sounds. Some gates let you keep what’s below the threshold and silence the strong partials, leaving a fascinating residue of the sound and any reverb tails.
  • Convolution is like multiplying the spectrum of one sound by another, like imposing the spectral envelope on the partials of another sound. It could be done instant by instant, resulting in a cross-synthesis hybrid of the two sounds. Convolution reverb (or sometimes just moving convolution) allows you to use one sound as the reverb tail for every FFT frame of a sound, allowing you to capture the reverberation of one space and apply it to another sound. Alternatively, if you use a rhythmic burst of noise instead of a reverb tail, the input sound will be copied in the same rhythm!
Variations Are Inevitable. Every process is going to give you slightly different controls.
  • Physical metaphors. A reverb might give you an imaginary room to mold instead of controlling the parameters listed above directly.
  • Stereo pairs. Some delays operate in stereo and define one channel’s parameters as percentages of the other channel’s parameters.
  • Combinations. Many elaborate processes will offer useful combinations of common processes. For example, it is common for a reverb to have a damping function (really a filter to reduce high frequencies) or a gate (to cut off long tails). A multiband compressor uses filters to divide your sound into separate frequency bands so it can apply different compression settings to each band. An aural exciter is usually just a high-pass filter run through distortion (to add odd harmonics) and combined with the original signal.
  • Modulation” (which just means “changing”). Some processes will offer to give your sound life by “wiggling knobs” for you automatically. They might let you pick a simple waveform as a pattern (e.g., sine, square) or random numbers. You’re likely to be offered controls for the rate of change and the modulation depth (how much to change, usually the amplitude of the wave you picked—but this time “amplitude” means the difference between maximum and minimum values and doesn’t necessarily mean loudness). A flanger is just a delay modulated in a sine wave pattern. A chorus is just a delay modulated randomly. A phaser is a very very steep notch filter modulated in a sine wave pattern (just to get the phase distortion effects of steep filter slopes). WARNING: Use repetitive modulation patterns (like sine waves) sparingly, or your music will sound nauseating, predictable, unnatural, or dated (70s or 80s). Keep modulation depths subtle, rates slow and out of sync with any metric or rhythmic pattern, and try breaking up predictable patterns with a gate.
  • Envelope. A process might let you sculpt parameters over time, but it will need to know when to start, e.g., when it detects an attack of a new sound, or when the loudness of a sound crosses a given threshold. See below for a more specific and common example.
  • Envelope Follower or just Envelope or just Follower. “Envelope” really just means “shape” in the abstract sense, but it is often used to refer to an amplitude envelope. An amplitude envelope follower will listen to the loudness of a sound and offer to use that to control some parameter of a processor. You’ll usually need to specify the range of values to use in mapping input loudness to the parameter at hand. When available, this is a terrific way to get some natural, musical variety in your sound automatically (in contrast to modulating parameters by sine waves, mentioned above).
Whenever encountering a new effects process, keep these basic parameters in mind, and seek them out (however they’re represented). New things will start to make sense a lot more quickly when you do.