T4.1: Mapping of AI algorithms in CH, initial digitisation, and preparation of datasets (Lead: CERTH; Contributors: All; [M04-M12]) – This task will be responsible for the mapping of existed AI algorithms that are applied in the sector of acoustics and musical CH, as well as potential adaptation from other fields that could offer empowered solutions in digitisation and analysis of dynamic processes, objects and complex combined data. In addition, partners will recruit and prepare existing datasets from the CH partners of the consortium and deliver it to the tech partners for early experiments and training of the systems. 3D and 2D digital representations will be some of them. In addition, this task will be the starting point for the following toolkits (TKs): TK4, TK5 and TK9. (Output: D4.1).

T4.2: AI for dynamic digitisation in acoustics and musical CH (Lead: TUIL; Contributors: IHU, UMA, FH, BEN#7, SCHUM, LUTHI; [M07-M18]) – This task focuses on the development of the first versions for TK3, TK4, TK5 and TK9. The methodologies that will be applied are M1.2.1.1, M1.2.1.3, M1.2.1.6 and M1.2.1.7. More specific, the task will involve the leveraging of advanced methodologies and tools for accurate and real-time digitization of acoustic profiles and musical artifacts. It will integrate acoustic profiling, monitoring and predictive modelling and machine learning-driven processes supported by AI algorithms. (Output: D4.2).

T4.3: AI for monitoring the evolution of musical CH (Lead: FH; Contributors: IHU, UMA, TUIL, BEN#7, SCHUM, LUTHI; [M07-M18]) – This task focuses on the development of the first versions for TK4, TK5, TK7 and TK9. The methodologies that will be applied are M1.2.1.2, M1.2.1.3, M1.2.1.4 and M1.2.1.5. More specific, the task will focus on applying artificial intelligence to track and analyse changes in the condition, acoustics, and material properties of musical artifacts over time. It will involve predictive modelling to forecast material degradation and sound quality shifts, cross-modal data integration for combining diverse datasets, and AI-based synthesis for generating realistic acoustic profiles. (Output: D4.2).

T4.4: AI for improved interaction in acoustics and musical CH (Lead: FH; Contributors: All; [M07-M18]) – This task focuses on the development of the first versions for TK6, TK7 and TK9. The methodologies that will be applied are M1.2.1.4 and M1.2.1.8. More specific, the task will focus on enhancing user engagement and interaction with musical heritage using advanced AI techniques. It will include immersive 3D visual and acoustic reconstruction to create engaging virtual experiences, cross-modal integration for seamless interaction between visual, acoustic, and tactile elements, and real-time AI-based synthesis to enable dynamic and responsive musical performances. (Output: D4.2).