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How "Tom's Diner" Tuned the MP3

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Suzanne Vega's catchy tune has made her "Mother of the MP3" -- though it took a while. Vega wrote "Tom's Diner" as an a cappella song way back in 1982. By 1984 it has been released on an obscure folk compilation, and didn't appear on Vega's studio albums until 1987's Solitude Standing. In 1990, the song was remixed by The DNA Disciples, adding a danceable beat and instrumentation -- this version hit the Billboard Hot 100, peaking at #5 in the US.

So what does this have to do with MP3? Well, after its release in 1987 audiophiles began using Vega's a cappella track to test speaker systems for clarity. It was considered a good, warm recording of a human voice -- something that could reveal flaws in an audio setup. Working at the Fraunhofer Society in Germany in the 90's, audio engineer Karl-Heinz Brandenburg was hard at work developing the MP3 audio compression scheme. Brandenburg used Vega's a cappella version of "Tom's Diner" to tune the compression system, playing the track before and after compression was applied to tell whether MP3 sounded good enough. He figured Vega's song would be a tough track to compress (as it was already favored by audiophiles), and would be a good test for whether MP3 was really listenable. Although many audiophiles ended up hating MP3, Brandenburg seems to have done pretty well for himself -- MP3 became an incredibly popular technology. On the choice of "Tom's Diner," Brandenburg recalled: "I was ready to fine-tune my compression algorithm...somewhere down the corridor, a radio was playing 'Tom's Diner.' I was electrified. I knew it would be nearly impossible to compress this warm a cappella voice."

In last week's New York Times, Vega reminisced about the song and her career as a "two-hit wonder" (the other hit was "Luka"). From her article:

So Mr. Brandenberg gets a copy of the song, and puts it through the newly created MP3. But instead of the "warm human voice" there are monstrous distortions, as though the Exorcist has somehow gotten into the system, shadowing every phrase. They spend months refining it, running "Tom's Diner through the system over and over again with modifications, until it comes through clearly. "He wound up listening to the song thousands of times," the article, written by Hilmar Schmundt, continued, "and the result was a code that was heard around the world. When an MP3 player compresses music by anyone from Courtney Love to Kenny G, it is replicating the way that Brandenburg heard Suzanne Vega."

So goes the legend. The reason I know what that MP3 originally sounded like is that last year I was invited to the Fraunhofer Institute in Erlangen, Germany, where I met the team of engineers who worked on the project — including Mr. Brandenberg, who I had met once before at the launch of the Mobile Music Forum in Cannes in 2001.

All the men are obviously intelligent, but Karl-Heinz is a character. He stands out, because he looks like a mad scientist. His hair and tie always look as if they have been blown askew in a stiff wind, and he taps the tips of his fingers together constantly, smiling beatifically.

Read the rest for one artist's thoughts on her nearly thirty-year career in music -- and the unexpected resonance of a song scribbled on paper back in 1982.

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iStock // Ekaterina Minaeva
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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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Nick Briggs/Comic Relief
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What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]

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