[dropcap]C[/dropcap]OMPUTER scientists have developed an artificial intelligence algorithm that can analyse and compare musical styles and have used it to study the musical progression of the Beatles.
Music fans and critics know that the music of the Beatles underwent a dramatic transformation in just a few years, but until now there has not been a scientific way to measure the progression, researchers said.
Scientists at Lawrence Technological University in the US had previously developed audio analysis technology to study the vocal communication of whales, and they expanded the algorithm to analyse the albums of the Beatles and other well-known bands such as Queen, U2, ABBA and Tears for Fears.
The study demonstrated scientifically that 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, which 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.
In popular music, albums are widely considered milestones in the stylistic development of music artists, and these collections of songs provide a convenient unit for establishing measurements to quantify a band’s progression.
The new study analysed 11 songs from each of the 13 Beatles studio albums released in Great Britain, and quantified the similarities between each song and all the others in the study.
The results for the individual songs were then used to compare the similarities between the albums.
The automatic placement of the albums by the algorithm was in agreement with the chronological order of the recording of each album, starting 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.”
The automatic association of these albums demonstrated that the computer algorithm determined that the songs on the first album, “Please, Please Me,” were most like the group of songs on the second album, “With the Beatles,” and least like the songs on the last album recorded, “Abbey Road.”
In this era of big data, such algorithms can assist in searching, browsing, and organising large music databases, as well as identifying music that matches an individual listener’s musical preferences, researchers said.
The study was published in the journal Pattern Recognition Letters.
