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Strum

Strum. Guitar Tuition Using Real-Time Pitch Analysis b y Richard Toner. Structure of Presentation. Motivation for the Project The Problem The Solution Technical Challenges Current Status Future Plans Demonstration Questions. Motivation for the Project.

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Strum

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  1. Strum Guitar Tuition Using Real-Time Pitch Analysis by Richard Toner

  2. Structure of Presentation • Motivation for the Project • The Problem • The Solution • Technical Challenges • Current Status • Future Plans • Demonstration • Questions

  3. Motivation for the Project • The art of learning to play the guitar • Requires dedication • Requires discipline • Daily practice is vital • This commitment has become a deterrent in the eyes of an easily bored generation • Guitar simulation games > Real guitars • I want to be better

  4. The Problem • What can we do to make daily practice a more enjoyable task? vs

  5. The Problem • What can we do to make daily practice a more enjoyable task? • Take inspiration from music simulation games • Blur the lines between tuition and gaming • Disguise daily practice as an enjoyable task • Existing software not sufficient • No evaluatory feedback

  6. The Solution • An application that allows guitarists to play their guitar in a game-like scenario • Display and play guitar tabs • Scores awarded based on performances • High score ladders • Technical exercises offered as challenges • Complete challenges to unlock other tabs

  7. Technical Challenges • Evaluation of guitar input • Requires pitch analysis to identify the pitch of the guitar signal • Does the pitch match the pitch of the current note in the guitar tablature? • Two major requirements • Must function in real-time • Must be accurate

  8. Digital Signal Processing • Choice of pitch detection algorithms • Time-domain algorithms • Some accurate • Computationally inexpensive • Frequency-domain algorithms • More robust than time-domain algorithms • Computationally expensive • Hybrid-domain algorithms • Highly accurate • Computationally expensive

  9. Digital Signal Processing • Choice of time-domain algorithms • Zero-Crossing Rate (ZCR) • Poor results with noisy signals • Commonly misclassifies the input signal • Autocorrelation Function (ACF) • Accurate • Able to run in real-time • Average Magnitude Difference Function (AMDF) • Accurate • Impervious to noise • Able to run in real-time

  10. Pitch Classifier • Uses JavaSound API to read guitar signal • Direct set-up from guitar to microphone port • Detects pitch using the AMDF • Classifies with 100% accuracy • Average classification speed of 27.246 ms • Calculates tuning error of signal • Required for guitar tuner application

  11. Main Achievements • Research & implementation of several PDAs • Implemented a real-timepitch classifier • Implemented a guitar tuner • Designed a guitar tab file format and parser • Designed a text interface for discrete play • Designed an Instrument-Driven Interface(IDI)

  12. Current Status • Text-based prototype developed for time-attack gameplay • Successfully reads and displays guitar tabs to play along with in real-time • Stores top times • Utilises IDI for menu navigation • GUI prototype currently incomplete • Offers MIDI playback of a tab • Real-time evaluatory feedback

  13. Future Work • Completion of GUI prototype • Chord recognition • Pitch Class Profile • Split-Signal Pickups • Alternative tunings • Virtual Studio Technology (VST) • Allow effects to be applied to a guitar • Tab editor • Allow users to create their own tabs

  14. Demonstration • Text-based prototype demonstration • Play a selection of tabs in time-attack mode • Try and achieve a top time by playing the tab as quickly as possible • Navigate the menus with the pluck of a string • Tune your guitar • Have a go if you want!

  15. Strum • Guitar Tuition Using Real-Time Pitch Analysis • Any Questions?

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