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3 Reasons for Syllabically Ambiguous Words

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Do you say car-a-mel or car-mel? Is your “fire” closer to fah-yer or fayr? There is a group of words in English that can be pronounced with two different syllable structures, depending on dialect, personal preference, or context of use. While many will insist that one or the other is incontrovertibly correct, there is usually no real basis for pronouncements on the one true syllable structure. Sometimes two things can both be correct. If you need a better authority than me on that, lots of dictionaries accept both pronunciations for all the words discussed below (e.g., Merriam-Webster). What’s more interesting than fighting about who’s right is understanding why these differences arise. There are three processes that result in syllabically ambiguous words.

1. Diphthongs, r’s, and l’s

One or Two Syllables: fire, tire, hour, liar, buyer, flower, drawer, layer, loyal, royal, file

All of these words have one- and two-syllable pronunciations. What do they have in common? They all have a diphthong followed by an r or l.

At least in their one-syllable versions. A diphthong is a glide from one vowel to another that takes place within one syllable. For example, the vowel sound in “hour” glides from “ah” to “oo.” A diphthong is not always represented in the spelling of a word. The vowel sound in “fire” glides from “ah” to “ee.”

The sounds that make up the second part of the diphthongs “oo” and “ee” can also serve as consonants when they start a syllable. “Win” starts in the “oo” position, but there, it is the consonant w. “Yes” starts in the “ee” position, but there, it is a y. (In technical terms, w and y are semivowels whose vowel/consonant status depends on whether they are in the nucleus of the syllable or at the edge of it.)

Sometimes the end of the diphthong becomes w or y, forming a second syllable. Hour becomes ah-wer and fire becomes fa-yer. This process also works in reverse. Sometimes a w or y moves over to join the vowel before it. Flo-wer becomes flour.

This kind of indeterminacy is all over the place. Think about “mower,” “shower,” “oil,” “hair,” “while,” or any other diphthong followed by l or r. Think of a one or two syllable pronunciation for each of them. Even if you think one of them sounds totally weird, you can imagine someone saying it.

2. Syncope

One or Two Syllables: orange, poem, crayon
Two or Three Syllables: caramel, mayonnaise, family, chocolate, camera, different, separate, favorite
Three or Four Syllables: interesting, comfortable
Four or Five Syllables: laboratory

These words all have a syllable which is often left out of the pronunciation. When we cut a sound out of the middle of a word, it’s called syncope (a three syllable word, sin-ko-pee). O-range becomes ornge, car-a-mel becomes car-mel, in-ter-es-ting becomes in-tres-ting. This pruning of syllables doesn’t happen in some random, haphazard fashion. If a vowel gets chucked, it will be before an r or l (those guys again!) or in some cases a nasal (m or n). It will also be from an unstressed syllable. So the American LA-buh-ra-to-ry becomes lab-ra-to-ry, while the British la-BO-ra-to-ry become la-bo-ra-try.

3. Epenthesis

Two or Three Syllables: realtor
Three or Four Syllables: mischievous

When we stick a sound into the middle of word, it’s called epenthesis. A few words gain extra syllables this way. Do you say mis-chi-vous or mis-chee-vee-ous? Real-tor or real-a-tor? Epenthesis usually happens in order to make something easier to pronounce—because some words can be as tricky as a mischievous realtor.

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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Name the Author Based on the Character
May 23, 2017
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