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Published byNelson Griffin Modified over 9 years ago
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BY: JOSH TABOR Applying Multilayer Perceptron Artificial Neural Networks to Recognizing Piano Keystrokes
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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
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The Plan Collect data (Middle C – Tenor C) Keys to be used
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The Plan (continued) Antialiasing Filter Downsample Sampled at 44.1Khz Highest f= 523Hz Downsample to 1200Hz Saves processing time Breakup signal
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The Plan (continued) Take FFT Average windows Label Develop ANN Test ANN
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Expected Results Expect it to work fairly well (90% classification rate) FFT cleaner than expected Performance degrades with SNR decrease
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