Raga Music Generation Pipeline: RagaCraft Our project, RagaCraft, bridges the gap between raw human emotion and the timeless art of raga music using cutting-edge AI. Here's a deeper dive into the underlying process: Customer Interaction: Users interact with our platform, sharing their current emotions and contextual information. For example, "I am feeling romantic today. It is Valentine's Day. I'd like a song to suit the mood." JavaScript Selection: Our system, powered by JavaScript, scans the user's input to select an appropriate raga that resonates with the given emotion. OpenAI Integration: To add depth and specificity, RagaCraft sends a refined request to OpenAI: "Generate a text-to-music prompt for a single romantic raga. Include parameters such as tempo, scale, pitch, and rhythm to optimize the romantic mood. Define ideal values for these features." OpenAI's Response: The API, enriched with musical knowledge, replies with precise musical direction. For instance, "For a romantic setting, employ the Hindustani raga Kamboji. Utilize a medium-slow tempo, major scale, and a high pitch with low undertones. The rhythm should be gentle with a 4/4 signature. Dynamics can vary, with crescendos and decrescendos, ensuring a light texture and smooth timbre." Audiogen Transformation: The detailed prompt from OpenAI is fed into Audiogen, which processes it and crafts a song that encapsulates the user's emotions. Delivering the Experience: Our user interface then presents the generated raga song to the user, completing a journey from raw emotion to personalized musical expression. Through RagaCraft, we're redefining the way users experience and interact with traditional music forms in the age of AI.
Category tags:Ifra Saleem
Data Engineer
Sreekanth Gopi
GenAI Data Scientist
Team member not visible
This profile isn't complete, so fewer people can see it.
Ayesha Kanwal
Ayesha Aslam
Developer, Graphic Designer ,Student
Devananda Sreekanth