<p class="jove_content">This study presents a reproducible somatosensory music-learning protocol combining residual LSTM recognition with TRPO for adaptive difficulty. It covers preprocessing, FFT features, training, personalization, and evaluation. On a public dataset, the hybrid model reached Acc 95.0 / P 93.5 / R 94.6 / F1 94.2 over three subject-disjoint folds.</p>

development-interactive-artificial-intelligence-tools-for

Development of Interactive Artificial Intelligence Tools for Personalized Somatosensory and Rhythm Evaluation in Intelligent Music Education Platforms

Traditional music education often lacks interactivity and real-time adaptability, especially in remote settings. This study introduces a personalized ...

Institution - Hefei College of Early Childhood Education

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