This week I met with Dr. Stern to ask some further questions about the\u00a0Phase Difference Channel Weighting (PDCW) source separation algorithm and the\u00a0Suppression of Slowly-varying components and the Falling edge of the power envelope (SSF) reverberation-reducing algorithm. In this meeting, I found a mistake in my previous implementation of the two methods.<\/p>\n
I spent time this week fixing my implementation in MATLAB. Instead of running and testing PDCW and SSF separately, as I had previously been doing, I switched to first running SSF on the two channels I intended to input to PDCW, then sending the two channels (now with less reverberation noise) through PDCW to separate out our source of interest.<\/p>\n
My goal before next week is to finalize a decision as to whether or not we can use only signal processing for source separation. If the SSF-PDCW combination works well enough, we will proceed with that, but if it doesn’t we will use the deep learning algorithm instead. If we use the deep learning algorithm, we may still be able to get better results by doing some pre-processing with SSF or PDCW \u2013 we will have to test this.<\/p>\n
This week I also wrote up a list of the remaining data we have to collect for our testing. We want to record the same audio in multiple different locations so having a written-out plan for testing will be useful in helping us get these recordings done more efficiently.<\/p>\n
I started planning out the final presentation this week and will finish that in the coming week.<\/p>\n
We are on schedule now and are working on integration and testing.<\/p>\n","protected":false},"excerpt":{"rendered":"
This week I met with Dr. Stern to ask some further questions about the\u00a0Phase Difference Channel Weighting (PDCW) source separation algorithm and the\u00a0Suppression of Slowly-varying components and the Falling edge of the power envelope (SSF) reverberation-reducing algorithm. In this meeting, I found a mistake in my previous implementation of the two methods. I spent time … <\/p>\n