Meng Jiang presented her work at a halftime seminar
Tuesday the 28th of May PhD-student Meng Jiang presented her work on a half-time seminar with the title "Array Systems for Sound Source Localization”. Now she will continue her work toward a doctoral thesis defense.
Meng Jiang is a PhD student in electronics working with sound source localization and classification. Her field of interest is designing tailored mixed methodologies to study “what is sounding where and when” with a focus on real-world experimentation measurement and application.
Abstract
This Half-Time Seminar Report presents the progress and future direction of research in sound source localization using array microphones. The first part of the report summarizes research results from 3 studies with 5 projects, addressing diverse aspects such as the investigation of novel approach of using ambient noise for silent object localization, the comparison of effectiveness of omni-directional and cardioid-directional microphones for indoor localization, further carry on the application of modified Array Manifold Interpolation for computational efficiency, as well as assist heart murmur diagnosis with array technique in cardiac auscultation, and the implications of improved measurement quality on the performance of pre-trained neural networks in sound classification. The second part of the report proposes continued research of this PhD study, for more accurate and efficient sound source localization. The second part research will focus on integrating MUSIC beamforming and Channel State Information (CSI) enhancements with machine learning to propose a real-time, machine learning-enhanced fingerprint method. These synergies between hardware, signal processing algorithms, and machine learning offer promising directions for applications in room acoustics and more, advancing the field toward more precise and adaptive sound localization solutions.