Yuqi Yang¹ and Yu Sun², ¹USA, ²California State Polytechnic University, USA

Music plays a vital role in therapy, offering a unique avenue for emotional expression and connection. This proposed project seeks to enhance the effectiveness of music therapy by leveraging natural language processing (NLP) techniques and machine learning to provide personalized song recommendations based on both emotional and narrative elements within lyrics, moving beyond traditional approaches that focus solely on emotional categorization [4]. By utilizing keyword matching algorithms, the project expands the scope of song selection, allowing users to explore music beyond predefined emotional categories [5]. The proposed system integrates with Firebase for efficient data storage and retrieval, while the Flutter framework facilitates the development of a user-friendly mobile application interface [6]. Through this interdisciplinary approach, the project endeavors to offer an accessible and automated music therapy experience.

Natural Language Processing, Machine Learning, Flutter, Mobile Devices