You’ve been at it for years. Every weekend you’ve ventured out and captured dozens of fresh field recordings. Now, your hard drive is bursting with sound effects. There are thousands. How do you sort them all? How can you find the clip you want?
The first place to start is by writing a good sound file name. Other metadata fields follow, such as description, track title, and others. Once you’ve captured many similar sound effects, it’s helpful to collect them all in one spot. This is done by placing similar clips within a category and subcategory.
What are the best sound effect category and subcategories? How do you name them? Is it better to have dozens, or a select, chosen few?
Today’s article explores those questions. It shares why categorization is important for large sound libraries. It delves into the theory behind sonic grouping. The post includes lists of sample categorization trees you can browse and use yourself.
Is sound library categorization really that involved? As it turns out, it is. I began writing this post expecting it would be a few brief points. As I got into it, I found there’s a lot to say about storing sound fx in their proper place. Three articles worth, in fact.
Here’s what we’ll look at in the first post:
- Why categorize sound effects?
- Nesting categories.
- Creating category names.
- Examples of sound fx categories.
Why Categorize Sound Effects?
Is there even a point to categorizing sounds? Is this really a step every sound librarian should bother with?
It is. Sound library categorization is an essential part of curating a clip collection.
Here’s why.
The First, Easiest Way to Find Sound Effects
Why bother adding categories and subcategories to field recordings?
It’s true, most of the time people find sound effects by searching with keywords. They’ll type “apache helicopter,” “metal crash,” or other terms into sound browsing software to find the clip they need. That’s the most popular way of finding sound effects.
Keyword searches can be powerful. Just like searching in Google, people can enter highly specific terms, use quotes to isolate phrases, type tilde to find similar meanings, and add Boolean terms (e.g., and, not, or) to produce highly specific results. Most commonly, though, people will search using one to three keywords.
That’s why searching by keywords often finds a blend of sounds. For example, “metal crash” could find results of a serving tray dropping as well as a car dropping in a junkyard. Those are obviously two radically different sounds from distinct categories: household and metal, perhaps. Discovering this diversity from keyword search results is useful for finding a variety of sounds, and also for sparking inspiration from creative juxtaposition as well.
The Power of Categorization
Searching by category and subcategory is a completely different approach. Why? It assumes a search begins by filtering. So, while basic keyword searches produce a wide set of results with little control, category searches show sound fx that are deliberately grouped.
This is helpful if you already know what you want. For example, if you need sounds from a 1999 Ferrari, you can simply find the “Vehicle/Ferrari” category and subcategory, and have everything already tidily arranged. So, category and subcategory searching is more useful the more precise your needs are. This method shines when searching for specific sounds: vehicle models, sounds from a particular city, clips from one breed or age of dog, and so on.
It is also a helpful contrast to the “catch all” results possible with keyword searching. How? It intentionally omits irrelevant sounds. Naturally, you won’t find birds in the shotgun category. There’s another benefit though. Searching by category deliberately highlights exclusion. How is this helpful?
Let’s imagine you’re searching for wind ambience. A “wind” keyword search would be too broad. It could bring up weather sounds (e.g., “wind blowing through dried corn stalks”) but it could also reveal improper results (e.g., “intersection traffic with wind gusts” or “music box gear winding”). The weather track is suitable, of course. The traffic or machinery tracks aren’t helpful, though, and clutter search results.
This is avoided by searching by category. Browsing the “Weather/Wind” category and subcategory reveals field recordings that focus solely on wind as a feature, not a problem. In other words, category searches present only clips that are the highlight of the sound, not supplemental to field recordings.
In a way, category browsing is a powerful, customized, highly-constrained keyword search.
Nesting Categories
The idea behind category organization is that similar sounds are grouped within them.
Imagine it’s time to do your taxes. You’re sorting receipts and invoices into file folders. Naturally, it makes no sense to have a separate file folder for every receipt. Perhaps it’s better to group them by each day? That’s possible, but that’s still quite broad with 365 folders. What’s better is to have a file folder collecting receipts and invoices for each of the 12 months.
It’s the same with sound effects. We cannot have a different category for every sound. That defeats the purpose of categorization entirely. What about a category for every vehicle type? That’s somewhat workable, but even categories for Bus, Car, Truck, Motorcycle, and so on will begin to sprawl. What is better is a single category: “Cars.”
Of course, placing all cars within this category is still quite broad. So, fx libraries use a second level of classification within the first, the subcategory. In our example, we could have separate categories for Bus, Car, Truck, and so on. The car subcategory would have a lot of sounds within it from many years, styles, and manufacturers. So, some car subcategories could be:
Category | Subcategory |
---|---|
Car | Cadillac Eldorado 1960 |
Car | Chrysler 300 Hemi 2007 |
Car | Ferrari 458 2011 |
Car | Various or Miscellaneous |
This process of tucking a specific term inside a more general one is known as nesting. It is also referred to as a category tree, named for the way thin branches (subcategories) spread away from the larger trunk (categories).
How deep should nesting go? The category and subcategory structure we use above is two level categorization. Should the subcategories have their own further subcategories? Should they be three levels deep? Five?
Two is usually best. Most metadata apps have two fields for categorization: category and subcategory. This makes sense online, too. The rule of Web e-commerce is that customers should find what they want in three clicks. Two-level categorization does the trick: one click for the category, the second for a subcategory, and the third to select the actual sound.
Broad and Narrow Categorization
We are surrounded by thousands of different sound types. That makes categorizing field recordings tricky. Why?
Well, let’s think about categorizing car sounds. There are thousands of models of cars, trucks, and buses. What’s the best way to categorize them? Here are ideas:
Option 1 | Option 2 | Option 3 |
---|---|---|
Bus | Vehicle/Bus | Greyhound Bus |
Car | Vehicle/Car | Dodge Car 1992 |
Dodge Car 2006 | ||
Truck | Vehicle/Truck | Mack Truck 18-Wheeler |
Mack Truck UPS Truck |
As you can see, the options seem endless. In reality, though, they all fall into two conceptual approaches: broad verses narrow categorization.
Broad categorization has a lot of categories, but fewer subcategories. Narrow categorization has fewer categories, but each of them will have many subcategories. Here are examples:
Narrow Categorization
Category | Subcategory |
---|---|
Animals | Bats |
Animals | Cats |
Animals | Dogs |
Animals | Horses |
Crowd | Indoor |
Crowd | Outdoor |
Crowd | Theatre |
Sports | Badminton |
Sports | Baseball |
Sports | Football |
Total: all sounds fit in 3 categories for 10 subcategories.
Broad Categorization
Category | Subcategory |
---|---|
Bats | Flying |
Bats | Squeaking |
Cats | Meowing |
Cats | Purring |
Dogs | Barking |
Dogs | Eating |
Dogs | Running |
Horses | Eating |
Horses | Walking |
Crowd Indoor | Lauging |
Crowd Indoor | Talking |
Crowd Outdoor | Footsteps |
Crowd in a Theatre | Applause |
Crowd in a Theatre | Intermission |
Sports Badminton | Hits |
Sports Badminton | Swing |
Baseball | Crowd |
Baseball | Glove Catches |
Baseball | Sliding |
Total: all sounds fit in 9 categories for 19 subcategories.
You get the point. Narrow categorization has fewer categories with many subcategories within them. Broad categorization has many categories, and the subcategories are far more specific. What’s best? Each has its own merits.
The idea behind narrow categorization is that it ensures swift selections. With fewer categories, a user can make a selection between them with less mental effort. It’s simple to skip from “Animal” to “Crowd” to “Sports.” Then, once inside the each category, it’s equally easy to “drill down” into a specific type of animal, crowd, or sport. Physically, it’s a smaller list to scan. And, with fewer options, decisions are easier and more swift.
The trade off? Subcategories can be vague. So, with the narrow categorization technique, the “Badminton” subcategory will have everything lumped into it: nets, hits, and swings.
Category | Subcategory |
---|---|
Sports | Badminton |
This is where broad categorization is stronger. Because it accommodates far more categories, the subcategories can be more specific. So, since we already have a “Badminton” category, its subcategories can indulge in detail: “Net,” “Hit,” “Racket,” “Swing,” and so on.
Category | Subcategory |
---|---|
Badminton | Hit |
Badminton | Net |
Badminton | Racket |
Badminton | Swing |
Category Rigidity
That shares another difference: category rigidity. Narrow categorization has fewer categories that don’t change much. Additional classification can be detailed in the subcategories, which are freely added. So, narrow categorization won’t add more than one “Sports” category, but will add many subcategories for different sports: “Badminton,” “Football,” “Soccer,” and others. Most of the changes occur in the subcategories.
Category | Subcategory |
---|---|
Sports | Badminton |
Sports | Football |
Sports | Soccer |
Broad categorization is far more liberal. New categories are added often. That allows for every type of sound category to be listed. As you’d expect, this method also allows list to sprawl.
Category | Subcategory |
---|---|
Badminton | Hit |
Badminton | Net |
Badminton | Racket |
Badminton | Swing |
Football | Goal Kick |
Football | Tackle |
Soccer | Dribble |
Soccer | Kick Ball |
That’s why narrow categorization is designed for swift decisions: it’s easier to scan across a list of 20 categories, make a decision, and keep refining in the subcategory.
Broad categorization is designed to provide ample detail: every conceivable sonic classification can be displayed in a combination of the category and subcategory.
Creating Category Names
OK, but how do you name your categories? Is it wisest to use “Transportation” or “Vehicle?”
It’s best to choose the most recognizable term people use to search. So, “Car” is better than “Automobile.” However, the precise term is really up to you, and what your audience expects.
There is one major decision, though: should you name with nouns or verbs?
Noun-Type Categorization
You’ll all remember the grade school lesson: nouns are people, places, or things. So noun-type category lists will include dart boards, budgies, and wheelbarrows. Verbs, however, are de-emphasized. That means “action words” like dropping, hitting, and so on aren’t included as main categories. The same applies for pops, crashes, or skids. Those terms are good, but too broad for main categorization. After all, a crash category may gather both wood and metal crashes, but in most cases an editor will be looking for one or the other. That’s why “Crashes” is a subcategory of both “Metal” and “Wood.” It keeps the sonic nature of them separate.
This tactic considers that people are searching field recordings for things: a boat, a hall, a patio crowd, and so on.
So, this type of categorization is good for field recordings or real world objects or places.
Verb-Type Categorization
When would you use verb-type categorization? Surely “Buzz,” “Hum,” and “Warble” would be good categories in some circumstances?
Yes. The verb-type categorization is very helpful if you use sound-designed clips. After all, it’s hard to definitively name a vibrating sound created by an outboard synth. Is the sound a sci-fi force field? Or maybe it’s a magic telekinesis spell? Who knows? For these clips, it’s much more helpful to label them by how they objectively sound, or what they are doing.
Verb-type categorization is great for sound design libraries of whoosh, UI elements, buzzes, and drones.
Examples of Sound Fx Categories
So, that’s the theory. Let’s see how others are using it.
Some prefer broad categorization. There’s only one classification, the category, and there are many of them.
The folks at Sounddogs use narrow categorization. There are 64 categories, each with a variety of subcategories.
- Sound Dogs categorization
- Sound Dogs subcategorization
Soundsnap uses a narrow categorization of 17 selections. Clicking each category shows text links of subcategories with a cool twist: the amount of sounds is displayed beside each link.
- Soundsnap categorization
- Soundsnap subcategorization
AudioMicro has an interesting blend. Their drop-down category list has 41 entires without any subcategories. The result? You can see each category has thousands of sounds within it.
You can also visit Amazon.com or eBay.com to see how categorization works on their sites. Amazon uses a single category structure, while eBay has up to four levels of subcategories. Browse these sites to find inspiration for what would fit best for your own sound library.
Wrangling Your Sound Collection with Categorization
Punching a trio keywords into Basehead may help find the best sound in small libraries. That won’t work for long though. You’ve been busy gathering audio year after year. That’s why, as your collections grows, you’ll need another tool: categorization. That helps filter results for specific requests quickly and tidily.
Categorization tucks clips within trees of classification. Will your list be broad with many categories and fewer, laser-sharp subcategories? Or, will it have a small amount of carefully chosen items with a diverse selection nested within them? Regardless of your approach, using noun- or verb-type classification will assemble your clips so the sounds you design and the field recordings you gather can be found and enjoyed by your fans.
Next: quick tricks and tips for creating and managing sound fx categories and subcategories.
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