Скачать или смотреть UR 445 - Symphony of Silicon: Rethinking Music Creation through Deep Learning Models

Generative AI has transformed music creation, blending human and machine artistry. This study presents a neural network model trained on piano MIDI files for music generation, utilizing LSTM and self-attention mechanisms to capture music's complexity. Bayesian optimization with Tree-structured Parzen Estimator (TPE) refines the model's hyperparameters. The architecture includes bidirectional GRUs and self-attention layers, trained on the extensive Magenta MAESTRO dataset. The model, bettered by TPE over conventional tuning, is assessed for accuracy and expressiveness. The paper details the model's design and validates TPE's efficiency, marking progress in AI's creative application in music.
Author: Gabriel T Gillott
Advisor: Dr. Hafiz Khan