" Shamir and graduate student Joe George had previously analysed the albums of other well-known bands such as Queen, U2, ABBA and Tears for Fears."
New York, July 25 - Computer scientists at Lawrence Technological University have developed an artificial intelligence algorithm that can analyze and compare musical styles, enabling research into the musical progression of the Beatles.

It demonstrates scientifically how the structure of the Beatles music changes progressively from one album to the next.

The algorithm works by first converting each song to a spectrogram - a visual representation of the audio content.

That turns an audio analysis task into an image analysis problem.

It is solved by applying comprehensive algorithms that turn each music spectrogram into a set of almost 3,000 numeric descriptors reflecting visual aspects such as textures, shapes and the statistical distribution of the pixels.

Pattern recognition and statistical methods are then used to detect and quantify the similarities between different pieces of music, explained assistant professor Lior Shamir from Lawrence Technological University in Michigan.

The automatic placement of the albums by the algorithm was in agreement with the chronological order of the recording of each album.

It starts with the Beatles' first album, Please, Please Me, and followed by the subsequent early albums, With the Beatles, Beatles for Sale and A Hard Day's Night.

Let It Be was the last album released by the Beatles, but the algorithm correctly identified those songs as having been recorded earlier than the songs on Abbey Road.

People who are not Beatles fans normally can't tell that 'Help' was recorded before 'Rubber Soul', but the algorithm can, Shamir said.

Shamir and graduate student Joe George had previously analysed the albums of other well-known bands such as Queen, U2, ABBA and Tears for Fears.

The study was published in the journal Pattern Recognition Letters.


comments powered by Disqus
Read more on:
 

PERMALINK

http://www.nerve.in/news:2535002390909
You can quote the permanent link above for a direct link to the story. We do not archive or expire our news stories.


STORY OPTIONS
  Email this story to a friend
  XML feed for Americas


 
COPYRIGHTS INFORMATION
All rights reserved for news content. Reproduction, storage or redistribution of Nerve content and articles in any medium is strictly prohibited.
Contact Nerve Staff for any feedback, corrections and omissions in news stories.
 

All rights reserved for the news content. Reproduction, storage or redistribution of Nerve content and articles in any medium is strictly prohibited.