Final Report

Video Lecture

Video, Slides

Description:

The Final Report Guidelines are the primary reference document for this assignment.

Requirements and Grading:

The Final Report is held to professional standards of language and format and is evaluated by staff in the ECE Editorial Services, who also check theses and dissertations for the department. The report is also evaluated for technical content and organization by the course staff. The Grading Rubrics are available for both English/Formatting and Technical Content , but here are some pointers:

  1. If you didn't click the link above, the Final Report Guidelines should be your first stop.
  2. Use a template to help get the formatting right (Microsoft Word template or LaTeX template).
  3. Since your Final Report is similar in purpose to a thesis, you may find the Thesis Writing Guidelines helpful for style and formatting.
  4. For citations, you may also find the IEEE Citation Reference guide useful.
  5. Please note the maximum number of pages (20) allowed for the final report. This does not include your references or appendices.You will be penalized for going over the maximum number of pages and/or not following the prescribed format.

    6. Submission and Deadlines:

    The Final Report document should be uploaded to My Project on PACE in PDF format by the deadline on the Calendar.

VoxBox Robo-Drummer

Craig Bost, Nicholas Dulin, Drake Proffitt

VoxBox Robo-Drummer

Featured Project

Our group proposes to create robot drummer which would respond to human voice "beatboxing" input, via conventional dynamic microphone, and translate the input into the corresponding drum hit performance. For example, if the human user issues a bass-kick voice sound, the robot will recognize it and strike the bass drum; and likewise for the hi-hat/snare and clap. Our design will minimally cover 3 different drum hit types (bass hit, snare hit, clap hit), and respond with minimal latency.

This would involve amplifying the analog signal (as dynamic mics drive fairly low gain signals), which would be sampled by a dsPIC33F DSP/MCU (or comparable chipset), and processed for trigger event recognition. This entails applying Short-Time Fourier Transform analysis to provide spectral content data to our event detection algorithm (i.e. recognizing the "control" signal from the human user). The MCU functionality of the dsPIC33F would be used for relaying the trigger commands to the actuator circuits controlling the robot.

The robot in question would be small; about the size of ventriloquist dummy. The "drum set" would be scaled accordingly (think pots and pans, like a child would play with). Actuators would likely be based on solenoids, as opposed to motors.

Beyond these minimal capabilities, we would add analog prefiltering of the input audio signal, and amplification of the drum hits, as bonus features if the development and implementation process goes better than expected.

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