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How "Tom's Diner" Tuned the MP3

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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Animals
Watch an Antarctic Minke Whale Feed in a First-of-Its-Kind Video
WWF
WWF

New research from the World Wildlife Fund is giving us a rare glimpse into the world of the mysterious minke whale. The WWF worked with Australian Antarctic researchers to tag minke whales with cameras for the first time, watching where and how the animals feed.

The camera attaches to the whale's body with suction cups. In the case of the video below, the camera accidentally slid down the side of the minke whale's body, providing an unexpected look at the way its throat moves as it feeds.

Minke whales are one of the smallest baleen whales, but they're still pretty substantial animals, growing 30 to 35 feet long and weighing up to 20,000 pounds. Unlike other baleen whales, though, they're small enough to maneuver in tight spaces like within sea ice, a helpful adaptation for living in Antarctic waters. They feed by lunging through the sea, gulping huge amounts of water along with krill and small fish, and then filtering the mix through their baleen.

The WWF video shows just how quickly the minke can process this treat-laden water. The whale could lunge, process, and lunge again every 10 seconds. "He was like a Pac-Man continuously feeding," Ari Friedlaender, the lead scientist on the project, described in a press statement.

The video research, conducted under the International Whaling Commission's Southern Ocean Research Partnership, is part of WWF's efforts to protect critical feeding areas for whales in the region.

If that's not enough whale for you, you can also watch the full 13-minute research video below:

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technology
AI Could Help Scientists Detect Earthquakes More Effectively
iStock
iStock

Thanks in part to the rise of hydraulic fracturing, or fracking, earthquakes are becoming more frequent in the U.S. Even though it doesn't fall on a fault line, Oklahoma, where gas and oil drilling activity doubled between 2010 and 2013, is now a major earthquake hot spot. As our landscape shifts (literally), our earthquake-detecting technology must evolve to keep up with it. Now, a team of researchers is changing the game with a new system that uses AI to identify seismic activity, Futurism reports.

The team, led by deep learning researcher Thibaut Perol, published the study detailing their new neural network in the journal Science Advances. Dubbed ConvNetQuake, it uses an algorithm to analyze the measurements of ground movements, a.k.a. seismograms, and determines which are small earthquakes and which are just noise. Seismic noise describes the vibrations that are almost constantly running through the ground, either due to wind, traffic, or other activity at surface level. It's sometimes hard to tell the difference between noise and legitimate quakes, which is why most detection methods focus on medium and large earthquakes instead of smaller ones.

But better understanding natural and manmade earthquakes means studying them at every level. With ConvNetQuake, that could soon become a reality. After testing the system in Oklahoma, the team reports it detected 17 times more earthquakes than what was recorded by the Oklahoma Geological Survey earthquake catalog.

That level of performance is more than just good news for seismologists studying quakes caused by humans. The technology could be built into current earthquake detection methods set up to alert the public to dangerous disasters. California alone is home to 400 seismic stations waiting for "The Big One." On a smaller scale, there's an app that uses a smartphone's accelerometers to detect tremors and alert the user directly. If earthquake detection methods could sense big earthquakes right as they were beginning using AI, that could afford people more potentially life-saving moments to prepare.

[h/t Futurism]

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