Bobbie
Done this week
This week I implemented speech-distortion weighted multi-channel Wiener filtering as described in “Multichannel Filtering For Optimum Noise Reduction In Microphone Arrays” (Florêncio and Malvar, 2001). The results are very strong in reducing noise, but also introduce a very noticeable distortion in the output signal. See the attached audio for an example.
This implementation processes the audio frame-by-frame, writing results to a buffer. For now, the buffer is simply written to file at script completion, but in an actual program it would be read from continuously for output. The 38 seconds of input were processed in ~3 seconds including file reading and writing; this implies that processing a frame takes at most about 70 milliseconds, which is within our time budget. The result shown involved some tweaking of the parameter P as well as the parameters for the least mean squares adaptive filter. I don’t see any glaring errors in my implementation of the algorithm, but the distortion levels are currently quite high and distracting. I will continue looking at this and trying to reduce the distortion, because the noise is reduced by about 24 dB.
Original input:
Post-MWF output:
I also generated some working C code using Matlab Coder. This was quite straightforward to do; Matlab Coder was able to automatically detect the types based on a script which used the relevant functions. We have the option of using Matlab Embedded Coder to generate directly for a ARM Cortex-M target, which may run faster because it will optimize for the particular processor we are using. However, we are not over on our timing budget yet, and it is useful to be able to see the C source code, so we will just use source code generation for now.
Goals for next week
- Reduce the distortion in the SDW-MWF implementation to a more manageable level
- Generate one HINT test to be run on the test environment
- Draft a parts list and diagram for the wearable mic array mount
Kevin
Done this week
This week I looked into how our team would go from our basic Matlab implementation, which consisted of LMS noise cancellation using a reference and primary signal, to using a microphone array. After looking through research papers, adaptive beamforming seemed to be a very promising.
The basic principle of adaptive beamforming is as follows. Beamforming microphone arrays are spatial filters that take multiple microphone signals as input and combine them to a single output signal. Usually the combined output is calculated by filtering each microphone signal through a digital FIR filter and summing the output of all filters as shown in the figure. The filters are designed so that their output add constructively when sound is coming from a specific direction (main lobe) and add destructively when sound is coming from all other directions. This creates the spatial filtering effect of focusing at the sound that is coming from the main lobe direction while attenuating sounds coming from all other directions.
Goals for next week
- Have a working implementation of beamforming
- Build temporary microphone circuit for testing (soldering microphones and designing circuit)
- Test on microphones that we received in lab
- Design actual microphone array for wearable
- (distance between microphones, what materials for mounting, etc.)
Sean
Done this Week
This week I fixed the PCB board so that we can order it through PCBway. This included manually adding layers that weren’t generated by the Eagle software and changing file encodings. I will order that as soon as I hear back from Quinn.
I have starting writing code for the Teensy to get simple inputs from the digital pins, where we will soon be inputting a signal from the microphones given to us by Professor Sullivan.
I did research on outputting a low-noise clock from the Teensy board, which can be done by clock-dividing the 16MHz I2S master clock. I also researched pulse density modulation on the Teensy board, which I found is included in the Audio library for the Teensy. Finally, I looked into power options for the Teensy. For now, we will use USB power, but the final product will need to have a portable battery pack, which we can set up with 2 or 3 AA batteries. Ideally, we’ll use a lower-profile, rechargeable battery for convenience and wearability.
Goals for Next Week
- Get signal through board using larger microphones
- Generate clock output on Teensy
- Begin using PDM library on Teensy
- Connect Teensy Audio Shield for audio output to headphones
- Figure out what method to use for external power so as not to damage the board when it is hooked up to the USB cable and an external power source.
Schedule
We have just missed a couple milestones on our schedule.
We have not sent a signal through the mics into the hardware system yet. The main delay here has been the very small mics we initially ordered and follow-on issues with PCB design. The PCB issues have been fixed and we should be able to order this week (waiting to hear back from Quinn). In the meantime, on Monday Sean will put together the larger microphones that Professor Sullivan lent us and get an actual input signal by then.
We also have not yet created a HINT Test which we can run on our test environment yet. This is mainly because there is not much point in creating one when the microphone-to-hardware connection to receive the signal does not exist yet. Bobbie will do this over the coming week.
Although these milestones were missed, we are not far behind in the project overall. This is because other non-blocked tasks in signal processing made progress when the tasks for the milestones above were blocked.
As another schedule-related concern, Sean will be travelling most of this week for interviews, and that may put his work slightly behind schedule. He will work diligently while he is gone to try to keep the project moving forward.