The impact of climate change on human and fauna and advances in sensing technologies have demanded and enabled environmental monitoring over large area and long period of time. Multiple networks have been set up around the world to monitor biodiversity using terrestrial acoustic sensors.
Timely and appropriate analysis of the big archive of environmental sound becomes a great challenge.
Research question: What are good ways to support human interaction with big data?
We will investigate the integration of the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers to form a powerful knowledge discovery environment.
This research will use the dataset the QUT BioAcoustic research group has collected over multiple years. Other big datasets, such as Amazon’s product reviews, could also be used.
- Review existing literature to gather related cutting-edge technologies for sound analysis and understanding in related fields such as acoustical signal processing, machine learning, visualization, ecology, and cognitive psychology. A comprehensive literature review report will be delivered.
- Design and develop a prototype platform that incorporates the latest technologies in related fields.
- Design and implement experiments using the dataset we have collected so far.
- Design new analysis techniques based on the above experimental results and findings.
Skills and experience
You should have background in the areas of either:
- computer science or information systems (computer human interaction)
- software engineering or signal processing.
You may be able to apply for a research scholarship in our annual scholarship round.
Contact the supervisor for more information.