Imagine a ten-year-old who hears a song and decides, for the first time, that she wants to learn piano. She's excited, motivated, ready to practice. But when she finds the sheet music, it's far too advanced. The pages of dense chords and rapid passages that would take years to master. Her options? Grind through beginner exercises that have nothing to do with the song she loves, or give up entirely. Most kids give up.
This scenario plays out millions of times every year, and it points to a fundamental gap in music education: the music people want to play rarely matches the music they're ready to play. What if technology could bridge that gap by automatically adapting any song to any skill level, creating a personalized path from the first lesson to full performance?
This is the problem Pedro Ramoneda has dedicated his career to solving. A researcher at the forefront of artificial intelligence and music, Ramoneda has developed breakthrough technology that can analyze how difficult a piece of music is to perform and then generate simplified versions tailored to a student's abilities. His work opens the door to a new era of truly personalized music education, where the curriculum adapts to the learner, not the other way around.
Ramoneda completed his doctoral research at the Music Technology Group of Universitat Pompeu Fabra in Barcelona, one of the world's leading centers for music technology, under the supervision of Professor Xavier Serra.
A talented pianist himself, he explains that his "goal was to reduce the gap between the motivational spark a musician has to learn a song and the available tools students, teachers, and institutions had to kindle that spark into a flame." His approach "places the performer at the center and understands music as a creative and educational activity, not only as a consumer product."
His research has earned recognition at the field's most prestigious international venues, including ISMIR, ACM Multimedia, and ICASSP, and has been published in leading academic journals. In 2024, Universitat Pompeu Fabra honored him with the Open Science Award for the best use of open data in a doctoral thesis. Dr. Dasaem Jeong, Professor at Sogang University in South Korea and one of Ramoneda's key international collaborators, describes him as "one of the world's most talented music information retrieval researchers," noting that his work "applying state-of-the-art AI/ML methodologies to music leveling has established himself as a global pioneer in the space."
Ramoneda's expertise has also attracted the attention of the world's largest music technology companies. Sony's Computer Science Laboratories in Tokyo funded a research internship where he worked on AI-powered music generation, and he completed additional research at Yamaha's R&D division focused on creating personalized practice exercises for students. These collaborations reflect a growing industry recognition that adaptive music technology represents the future of how people learn to play.
Now, Ramoneda is bringing his research from the lab to the real world. He recently joined
Songscription, a U.S.-based education technology startup whose mission is to "empower musicians worldwide to play, share, and learn the songs they love." The company has developed AI that can automatically transcribe audio into sheet music and recently raised funding to expand its research team. Andrew Carlins, Songscription's Co-Founder and CEO, explains the hire: "Most musicians—and most of our user base—are amateurs. Being able to turn any song into sheet music tailored for a specific level of play would be a complete game changer with the potential to finally make music accessible to millions of people who historically have been left out. We hired Pedro because we believed that if there was anyone in the world who could solve this problem, it was him."
The implications extend beyond Western classical training. Raman Khanna—Stanford University's former Chief Information Officer, current Managing Director of Dell Technologies Capital, and an angel investor in Songscription—sees potential for preserving and sharing musical traditions worldwide. "Indian classical music has been an oral tradition with limited ways to notate," he explains. "Songscription's technology creates a way to automatically transcribe ancient melodies so we can ensure they will be preserved for future generations. And if they can successfully develop technology that automates music leveling, it stands to make genres like Indian classical music more accessible to millions of amateur musicians globally."
For generations, music education has followed a one-size-fits-all model: standardized curricula, fixed progressions, and a long road before students get to play the music that inspired them in the first place. Ramoneda's research points toward something different: a future where learning music is as personalized as the playlists we listen to. That ten-year-old with a favorite song? She might finally have a way to start playing it on day one.