MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641063649 A) filed by Christ University on May 20, 2026, for A System For Profiling Musical Sophistication And Emotional Responses To Ai Generated Music And A Method Thereof For Predictive Assessment.
Inventor includes Christ University.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: As the number of transformer-based generative music applications, like Suno AT, lJdio, and Stable Audio, has rapidly increased, AT- generated music has become a ubiquitous component of modem digital media consumption, especially among Generation Z users on streaming and social media platforms. Despite this rapid cultural uptake, no standardized psychometric framework exists for systematically measuring how listeners of varying musical sophistication emotionally respond to AT-generated music under ecologically valid disclosed-authorship conditions. Existing music-emotion paradigms are predominantly validated on human- composed music, do not integrate sophistication profiling as a predictive variable, and lack standardized procedures for AT-stimulus validation. The present invention, namely "Musical Emotion-Sophistication Assessment for AT-generated Music (MESA-AIM)," is a system for profiling listener musical sophistication, eliciting emotional responses to validated AT-generated audio stimuli, and predicting systematic relationships between the two through a multi-stage psychometric pipeline. The proposed framework is classified into three phases. The first phase employs the Goldsmiths Musical Sophistication Index to generate a multidimensional sophistication profile across five theoretically derived subscales. The second phase generates, validates through inter-rater assessment, and presents a standardized AT-generated audio excerpt under disclosed-authorship conditions. The third phase captures music- induced emotions across the nine categories of the Geneva Emotional Music Scales and applies regression-based predictive mapping. Diagnosis of sophistication-emotion relationships is achieved through a combined feature analysis consisting of Subscale Profiling (Gold-MSI), Stimulus Validation (inter-rater kappa), and Emotional Response Mapping (GEMS-45 regression). This combined MESA-AIM framework yields a reproducible, cross-disciplinary assessment system applicable to streaming platform recommendation, generative-music quality evaluation, music therapy screening, and educational assessment.
Disclaimer: Curated by HT Syndication.
