Ear Machine EARs, hearing aid for iOS

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Ear Machine has announced the release of EARs, an app that turns an iPhone or iPod touch into a powerful, easy-to-use hearing aid.

Ear Machine EARs

With EARs, users can quickly manipulate the tone of the sounds around them by dragging a single dot around the screen.

“Every listening situation is different, so it’s important to be able to customize the tone as you move from one environment to another,” said Andrew Sabin, Ear Machine owner and psychoacoustics researcher. “EARs provides a simple interface where users can quickly get the sound quality they are looking for, and then get back to listening.”

EARs picks up sounds in real time using the iPhone’s built-in microphone or an external microphone. The sounds are processed according to where the user has placed the dot, and then sent out via earphones. EARs can also help if the user has different hearing in their two ears by providing separate controls for the right and left ears.

In the United States, only about one-third of the people who could benefit from a hearing aid actually use one, and self-contained hearing aids can cost as much as $3,000. “We hope that EARs will provide a convenient and affordable way for people with hearing loss to improve their hearing,” said Joshua Cooper, co-creator of EARs. “Even if you have normal hearing, EARs can enhance your ability to listen in difficult environments such as noisy restaurants or bars.”

EARs is for available to purhcase from the iTunes App Store for $3.99 USD.

More information: Ear Machine / EARs


Ear Machine iQ, equalizer plug-in learns the sound you like

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Ear Machine has announced iQ, an equalizer plug-in designed to learn the user’s preference.

Ear Machine iQ

iQ recommends equalizer settings by analyzing user ratings of examples. The result is displayed in a traditional equalizer window where users can fine-tune the recommendation.

“The idea for iQ came during a recording session when a client asked me to make the vocal track sound ‘buttery’,” said Andrew Sabin, Ear Machine owner and psychoacoustics researcher. “The client knew what he wanted, but wasn’t able to describe the settings that he was after. We designed iQ to help engineers communicate more easily with their clients, and to help beginning audio engineers figure out the sound they’re looking for.”

With iQ, users indicate how much they like each of a series of example settings by arranging dots from left to right, where each dot represents a different EQ setting. iQ uses a model of auditory perception to gradually hone in on the user’s preference. A meter at the bottom of the window indicates when iQ thinks it has learned what the user wants. The user then clicks “Create EQ” and iQ’s recommendation is displayed in a traditional equalizer window. Users can also double click any dot to display it in the equalizer window.

iQ is the first audio plug-in that is designed to learn a user’s preference. Ear Machine recently launched a related free web app (myMicSound) that is designed to learn a user’s preferred microphone characteristics.

iQ for Windows and Mac (VST/AU, compatible with RTAS wrappers) is available to purchase for $19.99 USD.

More information: Ear Machine / iQ


Ear Machine myMicSound, microphone recommendation engine

Ear Machine has launched myMicSound, a free web application that simplifies the difficult task of using your ears to decide which microphone to purchase.

Ear Machine myMicSound

The application learns the user’s preference by analyzing ratings of example microphones. myMicSound then returns a list that ranks microphones by the probability that the user will like their sounds.

“myMicSound is the first step toward a fundamental change in how people decide to purchase audio equipment,” said Andrew Sabin, Ear Machine owner and psychoacoustics researcher. “Currently, people make these decisions by receiving recommendations from friends, or by conducting a clumsily-organized listening comparison. myMicSound offers users a simple format to use their own ears to conduct a free, controlled, and comprehensive listening test.”

Users can either submit their own recording, or use one from myMicSound’s collection. myMicSound removes the sound of the microphone used to make that recording, and then simulates the sound of new microphones. myMicSound carefully considers factors influencing the sound of the microphone, such as the proximity to the sound source, the polar pattern, and whether filters are active.

myMicSound is the first sound-based recommendation engine in the audio equipment market. Its software algorithm relies on state-of-the-art knowledge in both auditory perception and computer science. Similar algorithms, such as the one used by Pandora, are widely used in music recommendation.

More information: myMicSound