PixelPlayer to Learn How Extract Musical Instrument

Massachusetts Institute of Technology scientists created new neural network
06 July 2018   1149

Scientist from MIT managed to create a neural network called PixelPlayer, which is able to indetify and extact the sound of individual musical instruments. The key feature of the development is the use of the method of spontaneous learning. This is reported by Analytics Vidhya.

In similar developments, the method of controlled learning was previously used. As input data, the AI ​​received marked audio files, the manual marking of which required a lot of time. PixelPlayer processes video - this allows to opt out of the preliminary preparation of information. Spontaneous training eliminated the human factor and accelerated the process.

Development involves three algorithms at once. The first processes the video, the second - the audio track, and the third synchronizes the data. PixelPlayer determines the sound pertaining to each pixel in the image. In this way, the neural network detects individual instruments and determines the melody to be released.

After 60 hours of training, the AI ​​was able to recognize with high accuracy individual melodies on new video recordings that had not been shown to it before. According to the developers, PixelPlayer is able to identify up to 20 different tools. This number can be increased by providing additional data for processing. Errors occur about trying to divide class-like instruments, for example, saxophone-alto and tenor.

PixelPlayer has already considerable potential for practical application. With this tool the quality of old live recordings can be improved. Amateur musicians often try to "remove" a certain party aurally, and the development of MIT scientists can simplify this task.

AI to Recognize Text Written by Invisible Keyboard

Developers said they tried to increase the typing speed on the on-screen keyboards
06 August 2019   147

Korean developers have created an algorithm that recognizes text printed on an imaginary keyboard on a touchscreen. Such a “keyboard” is not tied to a specific area on the screen, and the “keys” are not limited to clear squares.

As a result, a person types blindly in a QWERTY layout without thinking about where the keyboard should be and whether it got into the key.

Imaginary Buttons Press CloudsImaginary Buttons Press Clouds

According to the developers, they tried to increase the typing speed on the on-screen keyboards. The on-screen keyboard, unlike the hardware keyboard, does not offer feedback that confirms pressing. There is a risk to miss and not press the desired button. Because of this, people endlessly stare at the screen and eventually print more slowly.

The new algorithm allows you not to worry about this, you can enter text from memory, and the keyboard with 96% accuracy will guess what the person wanted to say. Tests have shown that the average typing speed on an imaginary keyboard is slightly less than on a hardware keyboard: 45 words per minute versus 51.