Smart drone audition: A search and rescue drone system that listens and communicates

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Dr. Benjamin Yen has integrated some of his research at the University of Auckland into related drone audition projects at the Tokyo Institute of Technology. Specifically, he incorporated techniques from his work in sound source enhancement to improve sound source tracking using multiple drones. This has yielded a conference paper submission to the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems. The paper is currently under review.We have submitted a journal article for drone audition to the IEEE/ACM Transactions on Audio Speech and Language Processing. Specifically, we proposed a noise covariance matrix estimation method that can be applied to sound source enhancement algorithms for drone audition. While this research is developed during Dr. Benjamin Yen's time at the University of Auckland, it is entirely within the research scope of the JSPS postdoctoral fellowship proposal and is a topic that will be further developed during this fellowship. The paper is currently under major revision.We have carried out a major outdoor experiment to collect the necessary data to perform performance evaluation for various drone audition algorithms. This includes accurate audio recordings of drone noise and a moving target sound source. In addition, accurate GPS data of the target sound source's movement is also recorded. These measurements will be helpful in evaluating sound source tracking performance from the algorithms proposed.We have planned a range of research topics related to the research theme to be researched by ourselves and new B4/masters students.