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Research Area/s:

SOUND-PROCESSING ALGORITHMS WITH PHYSIC-INFORMED MACHINE LEARNING TOOLS FOR SOUND-FIELD SYNTHESIS FUNDING ORGANIZATION: AGENCIA ESTATAL DE INVESTIGACION. PID2024-161353OB VIGENCY YEARS: 2025-2028 PRINCIPAL RESEARCHER: Alberto Gonzalez, Miguel Ferrer NUMBER OF PARTICIPANTS: 8 LINK:

Overview

SAPIENS-CONTROL pioneers the integration of Physics-Informed Machine Learning (PIML) into sound signal processing, particularly in Active Noise Control (ANC), adaptive filtering, and speech masking. PIML incorporates physical acoustics principles into learning models, enhancing accuracy, generalization, and efficiency. This research pushes PIML boundaries by embedding physical knowledge into data-driven models, optimizing adaptive filtering, and refining neural architectures for real-time acoustic processing.

For more info, see the project link.