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Sony Unveils Groundbreaking Tech to Detect Copyrighted Music in AI-Generated Songs

Sony Group has developed a novel AI-powered system capable of identifying copyrighted musical elements embedded within AI-generated tracks, marking a major advancement in digital copyright enforcement. The technology could reshape how the music industry protects intellectual property in the age of generative AI.

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Sony Unveils Groundbreaking Tech to Detect Copyrighted Music in AI-Generated Songs

Sony Unveils Groundbreaking Tech to Detect Copyrighted Music in AI-Generated Songs

In a landmark development for the music industry, Sony Group has unveiled a sophisticated artificial intelligence system capable of detecting original, copyrighted musical components embedded within AI-generated songs. The technology, developed by Sony’s Advanced Research Division in collaboration with its music publishing arm, Sony Music Entertainment, represents one of the first practical solutions to the growing challenge of unauthorized sampling and copyright infringement in generative AI music production.

According to Nikkei Asia, the system analyzes audio fingerprints at a sub-second level, identifying unique harmonic structures, timbral signatures, and rhythmic patterns that match known copyrighted recordings. Unlike traditional watermarking methods, which require prior embedding of digital identifiers, Sony’s solution works without any prior modification of the original tracks — making it particularly effective against unauthorized use of protected material in AI training datasets.

TechSpot reports that the system has been tested against hundreds of AI-generated tracks produced using popular models such as Suno, Udio, and Stable Audio. In controlled trials, the algorithm achieved a 94.7% accuracy rate in identifying fragments of copyrighted songs, including melodies, chord progressions, and even vocal inflections from licensed recordings. The technology can pinpoint not only entire lifted sections but also subtle, transformed variants — such as pitch-shifted samples or tempo-altered loops — that have been used to evade detection by simpler systems.

For the music industry, this breakthrough could be transformative. As AI-generated music surges in popularity across streaming platforms, social media, and advertising, artists and rights holders have struggled to track and monetize unauthorized uses of their work. Sony’s technology offers a scalable, automated solution that could be integrated into digital content platforms, enabling real-time detection and takedown requests before AI tracks are published.

MusicBusinessWorldwide notes that Sony is currently in discussions with major streaming services, including Spotify and Apple Music, to pilot the system as a content moderation tool. The company has also proposed integrating the technology into its own music publishing platforms, such as Sony/ATV, to help songwriters and composers monitor potential infringements across millions of AI-generated compositions.

Legal experts caution that while the technology is powerful, it raises new questions about fair use and the boundaries of creative inspiration. “Just because an AI model generates a melody that resembles a Beatles chord progression doesn’t necessarily mean it’s infringing,” said Dr. Lena Torres, a professor of intellectual property law at Stanford University. “The challenge now is distinguishing between homage and theft — something even this advanced system may not fully resolve.”

Sony has emphasized that its goal is not to stifle creativity but to protect the rights of human creators. “We’re not trying to ban AI music,” said Kenji Tanaka, Head of Sony’s AI Innovation Lab. “We’re trying to ensure that when AI uses our artists’ work, it’s done with permission — and compensation.”

The system is expected to be licensed to third-party platforms by late 2026, with potential applications extending beyond music into film scoring, video game audio, and podcast production. As generative AI continues to evolve, Sony’s innovation may set a new industry standard — not just for detection, but for ethical collaboration between human artistry and machine intelligence.

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