BY: JOSH TABOR Applying Multilayer Perceptron Artificial Neural Networks to Recognizing Piano Keystrokes.

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Presentation transcript:

BY: JOSH TABOR Applying Multilayer Perceptron Artificial Neural Networks to Recognizing Piano Keystrokes

The Project Create an MLP ANN to correctly identify which piano keys are pushed based on their FFT coefficients Test ANN at different noise levels and maybe on different pianos

The Plan Collect data (Middle C – Tenor C) Keys to be used

The Plan (continued) Antialiasing Filter Downsample  Sampled at 44.1Khz  Highest f= 523Hz  Downsample to 1200Hz  Saves processing time Breakup signal

The Plan (continued) Take FFT Average windows Label Develop ANN Test ANN

Expected Results Expect it to work fairly well (90% classification rate) FFT cleaner than expected Performance degrades with SNR decrease