{"id":3243692,"date":"2024-08-05T13:27:20","date_gmt":"2024-08-05T17:27:20","guid":{"rendered":"https:\/\/www.futurity.org\/?p=3243692"},"modified":"2024-08-12T09:18:18","modified_gmt":"2024-08-12T13:18:18","slug":"grammy-awards-songs-artificial-intelligence-3243692-2","status":"publish","type":"post","link":"https:\/\/www.futurity.org\/grammy-awards-songs-artificial-intelligence-3243692-2\/","title":{"rendered":"AI reveals clues about which songs win Grammy awards"},"content":{"rendered":"

New research uses artificial intelligence to identify traits of Grammy award-winning songs.<\/p>\n

Whether it’s the Oscars, the Tonys, or the Grammys, observers annually make predictions as to which actor, film, musical, or song will win these coveted awards\u2014with forecasts based on what experts say impresses the voters. “Grammy voters love to give Record of the Year to a carefully crafted throwback jam,” the Los Angeles Times<\/em> wrote ahead of this year’s Grammy Awards.<\/p>\n

A team of New York University researchers has systematized this process by creating an algorithm that takes into account a song’s traits, such as its lyrics, along with other information, including Billboard rankings, to illuminate the variables of successful songs<\/a>\u2014specifically, those voted as winners for Song of the Year, Record of the Year, and Rap Song of the Year in 2021, 2022, and 2023.<\/p>\n

In doing so, the work goes beyond some previous methods by not only making predictions, but also by identifying the traits of Grammy winners.<\/p>\n

“Spotting award-winning art is surely a subjective process and is complicated by the secrecy surrounding voters’ decisions,” says Anasse Bari, a clinical associate professor at NYU’s Courant Institute of Mathematical 糖心视频 and the senior author of the study in IEEE Xplore<\/em><\/a>.<\/p>\n

“However, by taking into account what we know about the songs themselves\u2014from their make-up to their popularity\u2014we can pinpoint those likely to be celebrated.<\/p>\n

“We think this AI tool could help to identify emerging artists and trends by unearthing music that is likely to be popular\u2014and that otherwise might go undiscovered.”<\/p>\n

In constructing the AI tool, the researchers created a dataset of nominees from 2004 to 2020 across three award categories\u2014Song of the Year, Record of the Year, and Rap Song of the Year\u2014totaling nearly 250 songs. They then combined a range of variables and trained AI algorithms to learn from these historical data, which included Billboard rankings and Google search volume (how frequently users searched for a nominated song in the year it was nominated).<\/p>\n

The algorithm also took into account a song’s musical characteristics, using Spotify<\/a> data deployed by previous studies, which included the following:<\/p>\n