Web Application
AI Product Programming
LyriGist AI
LyriGist AI
2025
Background
This project is based on the integration of Artificial Intelligence to identify song genres through their lyrics. The research focuses on developing a Machine Learning model capable of understanding song lyrics and their correlation with musical genres. The creation of this model stems from the unique and challenging nature of the music domain.
Background
This project is based on the integration of Artificial Intelligence to identify song genres through their lyrics. The research focuses on developing a Machine Learning model capable of understanding song lyrics and their correlation with musical genres. The creation of this model stems from the unique and challenging nature of the music domain.
Classical Machine Learning Based Model
The model used in this web app is a Support Vector Machine (SVM), a classical machine learning model. By using SVM, an accuracy of 66.45% was achieved on the lyrics dataset. Using such classical model allows lightweight predictions, increasing the User Experience and cost efficiency of this web app.
Classical Machine Learning Based Model
The model used in this web app is a Support Vector Machine (SVM), a classical machine learning model. By using SVM, an accuracy of 66.45% was achieved on the lyrics dataset. Using such classical model allows lightweight predictions, increasing the User Experience and cost efficiency of this web app.
Credits
Kent Timotheus
Theodore Zachary
Andoko Wijaya
Credits
Kent Timotheus
Theodore Zachary
Andoko Wijaya