Songs are no longer made like they used to be. And this is not only said by music critics who lived through the musical revolutions of the 1960s and 1970s when they were young, out of nostalgia. This is confirmed by a study that has analyzed the greatest musical hits of each year in the United States, from 1950 to 2022. Its conclusion is that the melodies of the most popular songs are increasingly simple and repetitive. However, the researchers clarify that this does not mean that the hits Today’s musicals are not only worse or poorer musically, but they have found complexity and richness in other elements other than melody, which are less obvious.
Although for the general public the melodies are what most stands out in pop music, science has little studied the ingredients that determine its success. Madeline Hamilton, lead author of The new research published this Thursday by the magazine Scientific Reportsshe wanted to dedicate her doctoral thesis to this. “I would say that the melody, especially the main vocal melody, is the most significant dimension of a song. Usually, it is what we remember about it and what you sing or whistle when you are listening to it; and not the bass line or the drum beat,” says Hamilton. That is why she thought she should start there when she set out to investigate “why we like the music we like, and how we could predict whether a person is going to enjoy a particular piece of music.”
Then a “happy accident” happened, in the words of this researcher. When she began to look into melodies and analyze them, she first noticed that over the years the number of musical notes per second was increasing. And then she discovered something she wasn’t looking for: she saw how the parameters she used to measure the complexity of melodies had been decreasing since the 1950s. In that decade, songs like In the blue dipped in blue (Volare)with which Domenico Modugno was number one in the USA, won the San Remo Festival and came third at Eurovision in 1958.
Hamilton wanted to confirm his chance discovery and to do so he carried out a more in-depth analysis, together with Marcus Pearce, his supervisor at the Music Cognition Laboratory at Queen Mary University of London. The first big challenge was to build his own catalogue of high-quality and detailed musical transcriptions; until then there was not one that was sufficiently extensive, and this greatly limited the quantitative study of the melodies.
Most previous research in computer science applied to music had been carried out directly from audio clips of songs, which reduced the study to very basic elements, such as the tempo of the songs or the timbre of the instruments that appear. The analysis of these characteristics is already quite automated and, with the help of artificial intelligence, is used by the services of streaming —like Spotify, Tidal, or Apple Music—to suggest songs similar to the ones we’re listening to.
A very musical confinement
In order to go further and scientifically study something more abstract, such as melodies, Hamilton had to dedicate herself to the meticulous task of manually transcribing the vocal part of the songs. She did this during the first year of the pandemic, coinciding with a lockdown in London. “For two months, I dedicated about 10 hours a day to this task of intense concentration and attention to detail. At that time, I didn’t have anything better to do than sit in my room transcribing music,” recalls the researcher.
After six months, she finally finished recording the notes and rhythmic structure of the most popular melodies of the last seven decades. Her catalogue includes the five biggest hits of each year according to the American singer. Billboard Hot 100which is the most famous music list in the world and is based on record sales, digital listening and radio plays. Later, he polished and expanded that catalog, which is available online for public use and now spans from 1950 to 2022: it contains a total of 366 songs, with their melodic fragments encoded in more than 1,000 digital files in MIDI format.
Hamilton and Pearce subjected all this material to statistical analysis using algorithms for detecting change points. They looked at eight parameters that allow the melodies to be described with data. And using sophisticated computer calculations they were able to confirm their initial discovery that the melodies have become simpler over the last seven decades. And unlike what happens with other elements, previously studied, such as the harmony and timbre of the instruments usedThey observed that in the evolution of melodies there are no cycles in which trends come and go, but rather the reduction of complexity has been a constant.
In their article, the researchers also highlight that there were two very sharp drops in melodic complexity around 1975 and 2000. The authors attribute this to the influence of new styles such as disco music or hip hop, respectively, on popular songs. They also found a significant increase in melodic repetitions within songs over the last two decades, which they relate to the loopsThese sound loops were first characteristic of rap and have now become widespread in pop music.
After confirming that songs like those of the past are no longer being made, the researchers stress in their article that the scientific evidence found does not allow us to say that today’s big hits are worse. And finally, they suggest that “a possible cause for the simplification of melodies is that it is a response to an increase in complexity in other aspects.”
That is, it would be an evolutionary adaptation to a musical world in which faster songs triumph—with a greater number of notes per second—with multiple layers of voices and instruments and with a production that takes care of the quality of the sound in detail. Thus, the only way to avoid overwhelming and disturbing listeners is to simplify the melodies. “For example, using small intervals between notes, a limited range of tones and a lot of repetitions,” explain Hamilton and Pearce. This is what happens in songs like Bad Guyby Billie Eilish, which reached number one in the US in 2019.
However, the authors acknowledge that we need to go much further than just analysing the five biggest hits of each year. Hamilton is already working on expanding his catalogue of the most successful melodies and is confident that, with the current push from generative artificial intelligence, “in a few years we will be able to make automatic transcriptions of the melodies while maintaining high quality.” With this help from AI, he could provide more complete scientific interpretations of the evolution of music and, perhaps, return to his original idea of discovering why we like the music we like.
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