RPI ID: 2020-009-401
Innovation Summary: A Bayesian framework is introduced for enumerating sound sources and estimating their direction of arrival (DOA) in complex acoustic environments. The system models spatial audio data probabilistically to distinguish overlapping sources and infer their positions with high accuracy. It supports dynamic environments and varying noise conditions, making it suitable for real-time applications. The method is adaptable to microphone arrays and embedded audio systems.
Challenges / Opportunities: Traditional DOA estimation techniques struggle with multiple simultaneous sources and noisy conditions. This invention addresses those limitations by leveraging Bayesian inference to improve robustness and precision. It opens opportunities for enhanced audio scene analysis, smart devices, and surveillance systems. The framework supports integration with consumer electronics and autonomous platforms.
Key Benefits / Advantages: ✔ Accurate multi-source localization ✔ Robust to noise and interference ✔ Real-time processing capability ✔ Compatible with microphone arrays ✔ Scalable for embedded systems
Applications: • Audio scene analysis • Smart speakers and devices • Surveillance and monitoring systems • Autonomous navigation
Keywords: soundlocalization #bayesianinference #directionofarrival #audiosceneanalysis #microphonearrays #embeddedAI
Intellectual Property: US Issued Patent, US12386007B2