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The purpose of this project is to create a useful tool for musicians that utilizes the harmonic content of their playing to recommend new, relevant chords to play. This is done by training various Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) on the lead sheets of 100 different jazz standards. A total of 200 unique datasets were produced and tested, resulting in the prediction of nearly 51 million chords. A note-prediction accuracy of 82.1% and a chord-prediction accuracy of 34.5% were achieved across all datasets. Methods of data representation that were rooted in valid music theory frameworks were found to increase the efficacy of harmonic prediction by up to 6%. Optimal LSTM input sizes were also determined for each method of data representation.
My proposed project is an educational application that will seek to simplify the<br/>process of internalizing the chord symbols most commonly seen by those learning<br/>musical improvisation. The application will operate like a game, encouraging the<br/>user to identify chord tones within time limits and award points for successfully<br/>doing so.
Madit Deng Ring Elyel was born to a small farming family in northern South Sudan.
“Lost Boys Found” is an ongoing, interdisciplinary project that is collecting, recording and archiving the oral histories of the Lost Boys/Girls of Sudan. The collection is a work-in-progress, seeking to record the oral history of as many Lost Boys/Girls as are willing, and will be used in a future book.
Kueth Yul (Nuer) was born in the spring when the nation was in peace talks that very soon collapsed into violence.
“Lost Boys Found” is an ongoing, interdisciplinary project that is collecting, recording and archiving the oral histories of the Lost Boys/Girls of Sudan. The collection is a work-in-progress, seeking to record the oral history of as many Lost Boys/Girls as are willing, and will be used in a future book