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<\/p>\nThis past week I spent some time finalizing my prep for the final presentation, then I moved to focus on working on our poster and planning testing. I picked up our new mics, which we were able to test out on Friday. The new mics take noticeably better recordings than our UMA-8 array.<\/p>\n
Before the Friday testing, I wrote up the tests that we should perform, how many times we should perform them, and created a spreadsheet to keep track of our tests and results so that we could get through data collection and analysis more efficiently. I decided on 3 trials per test, as this is a standard minimum number of trials for an experiment.<\/p>\n
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In our last meeting, Dr. Sullivan gave us some advice as to how to test our system more effectively, and I incorporated that advice into the new testing plan. For one, Larry and I used the same script as each other for this round of testing. In test 7, where we spoke at the same time, I started on sentence 2 and spoke sentence 1 at the end, and Larry started on sentence 1. Initially we tried simply speaking the same script starting from the top, but Larry and I were speaking each word at the same time, so the resulting word error rates would not have been a good measure of our system’s ability to separate different speakers.<\/p>\n
Another testing suggestion I added for this round was having a reversed version of each test, so that we could tell if there was any difference between word error rate for my voice (higher pitched) vs. Larry’s voice (lower pitched).<\/p>\n
One suggestion that we have not yet used is testing in a wider open space, such as an auditorium or concert hall. For the sake of time (setup and data collection took 3-4hrs), we decided to only get conference room data for now.<\/p>\n
We are currently on schedule.<\/p>\n
On Sunday, I will complete the poster. Next week, I will generate the appropriate audio files and calculate WER for the following sets of processing steps:<\/p>\n
0. Just deep learning (WERs already computed by Charlie)<\/p>\n
1. SSF then deep learning, to see if SSF reverb reduction improves the performance of the deep learning algorithm<\/p>\n
2. SSF then PDCW, to see if this signal processing approach works well enough for us now that we have better mics<\/p>\n","protected":false},"excerpt":{"rendered":"
This past week I spent some time finalizing my prep for the final presentation, then I moved to focus on working on our poster and planning testing. I picked up our new mics, which we were able to test out on Friday. The new mics take noticeably better recordings than our UMA-8 array. Before the … <\/p>\n