This week was my last one and I finished up my part of the code for the audio REScue project. I was in charge of the signal processing for the study and I was able to create moving sounds based off the testing conditions. While the study isn’t all the way finished, we’ve made a lot of progress. I spent the rest of the week writing my final report and uploading my files into the lab drive for them to ue when we’re gone.

This week we started coding the study we created last week. We’re building the project in MatLab and are using different toolkits to implement our ideas. I’m focusing on the backend and the signal processing while my partner is working on the user interface. The split worked out really well because we’re both working on what we’re interested in. We also ran our focus group with the firefighters from Gainesville Fire and Rescue. It went great! We learned a lot about how S&R operates in the real world along with how tech could improve it.

This week we finished designing the methodology for the moving sound experiment to be implemented in MatLab. The study is a Within-groups Study (Repeated Measures). The sound is a moving object (a triangle wave at 400Hz) starting somewhere in front of the participant and moving left or right. The independent variables are movement speed (10°/s, 20°/s, 40°/s, 80°/s, 160°/s, and 320°/s), distance (near field and far field), noise ratios (0%, 50%), and angular movement ( 5°, 20°, 40°, 60°, 90°, 120°). I’m in charge of the signal processing and backend of the project.

This week we continued thinking about how we were going to design our portion of the study. The study is to determine what rate of 3-D sound movement can be reliably detected. A sound can be detected reliably if its starting position and ending position can be determined within 5 degrees of error. We spent a lot of time reading papers to understand common methods for testing this accuracy. We found a couple studies and decided to implement methods similar to Han & Chen (2019). We plan on coding a prototype of the study in MatLab next week.

This week we finished running our first studies and developing focus group questions for the Audio REScue project. We also got our first programming assignment. My partner Michael and I were tasked to come up with a study to test what rate of 3-D sound movement can be detected in real-world situations. Today we spent the day reading papers on the subject and brainstorming how we could test for our question.

This week I continued running studies for Audio REScue and gathered more information on firefighters. On Thursday, our PI Dr. McMullen came in and we presented what we learned about firefighter search and rescue. She and Armisha gave us notes and direction for what to keep and what to change. We also started developing questions for a focus group we’ll be holding for the Gainesville Fire Department.

This week I continued running studies for Armisha and started gathering information about firefighters. Dr. McMullen and Armisha are the PI and Co-PI for a research project called CAREER: Audio RESCUE. They’re looking for a way to use 3-D audio to aid first responders in complex environments. We’re planning on testing these ideas with local firefighters. My job this week was to find out what firefighters do during search and rescue operations.

This week, I started learning MatLab using an online course through Linkedin Learning. The course taught me the basic syntax of the language along with ways to use it for my research. We plan to use this knowledge to develop new studies. I also got started helping Armisha Roberts - a PhD student with her lab tests. She’s running a study to see which sonic cues affect sound source localization and I’m in charge of proctoring the test with my partner. Outside of that, I’m trying to pick up as much signal processing knowledge as I can while I’m here.

This week, I familiarized myself with the nature and application of sound - specifically 3-D audio. I learned the physics behind sound waves and applications of the fourier transform / fast fourier transform. I then studied the ways natural spatial hearing is digitally simulated in 3-D audio systems. I learned about the methods in which sound images are manipulated and the difficulties that can come with these methods. I also spent time learning how to use MatLab and its application for signal processing.