Undergraduate team capstone
ALDA
An assistive guitar-learning prototype combining audio capture, chord recognition, and servo-controlled laser guidance.
My contribution
Primary hardware design, assembly, integration, calibration, and testing; supporting machine-learning work
Problem
Beginning guitar players must translate chord diagrams into finger placement while checking the sound they produce. ALDA explored combining visual fretboard guidance and audio feedback in one attachment.
Context & contribution
Assistive Learning Device Attachment for Guitars — a team capstone at Mapúa Malayan Colleges Laguna, developed with two teammates.
- Took primary responsibility for hardware design, assembly, and integration, including wiring, soldering, and troubleshooting.
- Integrated the piezoelectric pickup, signal-buffer circuit, USB sound card, display, and power connections.
- Assembled and calibrated six servo-controlled laser modules using a PCA9685 PWM driver and relay switching.
- Assisted with the machine-learning component and contributed to integration and prototype testing.
Engineering decisions
- Establish usable digital audio input before evaluating the team’s chord-recognition component.
- Calibrate servo positions and physical mounting against the actual strings and frets, rather than checking movement alone.
- Add a support strap during prototype testing to help stabilize the mounted assembly and maintain alignment.
Testing
Integration checks covered audio input, recognition output, servo positioning, laser alignment, and connectivity. Prototype evaluation collected feedback on usability, effectiveness, reliability, and satisfaction; no model-accuracy or performance claim is made here.
Outcome & limitations
The team demonstrated a prototype combining audio processing, recognition, and physical fretboard guidance. Feedback on setup and guidance clarity included positive responses, while usability, recognition performance, and consistency needed improvement.
- Weight, mounting stability, comfort, recognition consistency, and interface design remained challenges.
- Lighter housing, external projection support, improved interfaces, and expanded learning modules were proposed future work.