Abstract:
This project describes the development of a web application that uti! izes Al to create a Beat Generator which allows users to generate music beats using their voice or by select ing their preferred mood and music genres. The technology incorporates advanced AI machine learning techniques, where the system initially captures the samples of the user's voice inductive looping,. Then it uses their features and employs a voice Random Forest classifier to gauge the mood of the voice. Moreover, a user can also choose a certain mood and genre, and the system will tailor the beat generation according to the choices made. A backend consists of several models that work in synergy, including classifiers based on mood and type of loop, as well as classifiers predicting the tempo, which work together to optimally c lasifery and unify audio loops from their extensive libraries. The obtained beats undergo further step of audio processing to make sure that the output is polished and up to standards. Following modem music platforms, the frontend interface designed was constructed around Board GUI "It's consisting out of the touch card GUI, where every generation mode has its own interactive card, levelighted equalizer showing in real-time, logiclally alphabetical sound equalizer seasoned to manipulate the sound's blend of the output stream, and listening to multi-voiced out." With Al,digital s ignal processing, and responsive design working in iluid conjunction, this encourages the exceeds spoken boundaries, proving a profound tool for both requirements and technology voyages. As presented in the past sections of digital are the showpieces of machine learning infused with web technologies to facillitate the production of music and navigate creators to new landscapes of musical expression.
