This week I worked on training the CNN with extra preprocessing. First, the audio files were previously trimmed to be 5 seconds long, and also passed through Eri’s Shannon Expansion noise removal algorithm. I then took the spectograms of this new processed audio data and trained my CNN on it. Since the spectograms were now all of the same time frame of 5 seconds, we expected our accuracy to go up. However, the newly trained CNN produced an accuracy of around ~65%, so it was a decrease from the previously trained CNN’s with the same number of audio files. More testing has to be done on how to improve this algorithm.
I was travelling last week and this Sunday-Monday for interviews and Spring Carnival was this weekend, so I could not invest too much time into this project this past week. However, more time will be invested in future weeks to ensure that we reach the desired 85% accuracy by final demo. Next week I want to research LTSM to preprocess the data instead of trimming at a random 5 seconds length.