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Team Acoustic Beamformer

Preliminary Design Review. Team Acoustic Beamformer. 10/18/2013. Team Acoustic Beamformer. Name. Jimmy Danis EE. Nick Driscoll EE. Rebecca McFarland CSE. John Shattuck EE. Presentation Overview. Problem Statement Social Impact Our Project: The Acoustic Beamformer

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Team Acoustic Beamformer

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  1. Preliminary Design Review Team Acoustic Beamformer 10/18/2013

  2. Team Acoustic Beamformer Name Jimmy Danis EE Nick Driscoll EE Rebecca McFarland CSE John Shattuck EE

  3. Presentation Overview • Problem Statement • Social Impact • Our Project: The Acoustic Beamformer • System Requirements • Block Diagram • Description of Components • Alternatives • Current Development Status • MDR Deliverables • Schedule

  4. Problem Statement • Difficult to scan and localize a single person’s voice among outside conversation and background noise in real time

  5. Problem Areas • Primary: Conference Rooms/Small Lecture Halls • Video conferences across business sites • Questions asked in lecture • Secondary: Surveillance • Detecting noises in small rooms • Would be nice for surveillance cameras to quickly point to an intruding noise source

  6. Social Relevance • Hard for those with hearing impairments to filter out background noise • Cost considerations • High-end hearing aids can cost up to $8000 • Up to 75% of hearing-impaired individuals do not have hearing aids

  7. Solution: The Acoustic Beamformer Input: 8microphone outputs Output: Project audio signaland visual representation of sound wave UtilizeBeamforming Signal Processing Techniques

  8. System Requirements • Operate within the human voice frequency spectrum • Ideally 300 Hz- 3kHz • Localize a sound source within 5 meters of the microphone array (15 feet) • Effective in an 100 degree span 15 ft. (Not to Scale) 40o

  9. Final System Functionality • Initial Goal: • Manually input desired target angle into the PC • Optimal Goal: • Scan, find and fixate on individual sound sources within our 100o span • Alternative: Identify an electronic “bug” emitting a high frequency sound (15kHz) to fixate on

  10. Block Diagram

  11. Microphones • Analog Device MEMS Microphone • Omnidirectional • Analog output • Frequency range: 100 Hz – 15 kHz • Sensitivity -42 dB +/- 3 db @ 94 dB SPL • S/N Ratio 62 dB

  12. A-D Converter • Need 8 channel inputs • Need USB out because modern computers do not support serial interfaces • Options we are investigating: • MC USB-DIO24/37 DATAQ DI-149 USB

  13. Computer Software • MATLAB for simulation and initial analysis • Custom software for real-time processing • DSP processing library • Visualization • Audio output

  14. Alternatives: Nontechnical • Direction of interest manually fixated • Pass around a microphone • Physically turn a microphone or camera to target point • Cheap and accessible • Inefficient, more time consuming than electronic methods

  15. Alternatives: Technical • ClearOne non-directional 24 microphone array for conference rooms • Price: $3,000 • Polycom HDX Ceiling Microphone Array • Price: $1,200 Systems are expensive, far exceeding an SDP budget

  16. Current Development Status • Researched similar previous SDP projects • 3 main issues keeping others from succeeding: • Problems integrating A/D Converters • Choosing substandard microphones • Assuming plane waves (sources likely too close) • Compiled several MATLAB simulations • Refining a basic algorithm for use • Purchased a few microphones for initial testing before deciding on final hardware

  17. MATLAB Plots

  18. MATLAB – Source Angle Sweep

  19. Proposed MDR Deliverables • Single microphone to A-D • Input into MATLAB • Be able to analyze one channel in MATLAB • Parallel development of real-time software framework

  20. Schedule

  21. Backup Information

  22. Mic Separation Sweep

  23. Source Frequency Sweep

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