Welcome to HarmoniGraph, is an innovative project aimed at revolutionizing the way music is written by leveraging a comprehensive knowledge graph that interlinks lyrics, themes, melody, harmony, and other musical elements. Our goal is to provide songwriters and composers with enriched insights and tools to create music that perfectly aligns with their lyrical intentions.
HarmoniGraph seeks to develop a detailed knowledge graph encapsulating the complex relationships within music, from lyrical content to musical composition. By integrating machine learning and natural language processing, we aim to uncover patterns and insights that inspire and support the creative process of songwriting and composition.
- Knowledge Graph: An intricately designed graph that connects songs, lyrics, themes, musical elements, artists, and genres.
- NLP and Thematic Analysis: Advanced processing of lyrics to extract themes and sentiments, enhancing thematic connections.
- Musical Element Analysis: Identification and categorization of melody, harmony, and rhythm within the graph.
- Machine Learning Predictions: Predictive modelling to suggest suitable musical elements for new lyrics based on existing patterns.
- Creative Songwriting Tool: A platform for songwriters to generate songs with coherent themes and musical arrangements.
- Data Collection: Assembling a comprehensive dataset from various sources and APIs.
- Lyrics and Theme Analysis: Employing NLP techniques to process lyrics and identify thematic elements.
- Musical Analysis: Analyzing musical components to be included in the knowledge graph.
- Graph Development: Constructing the knowledge graph using graph database technologies.
- Insight Generation: Utilizing the graph to derive patterns and insights for songwriting.
- Predictive Modeling: Developing and applying models to suggest musical elements for lyrics.