Rāgawise: a Lightweight Real-time Rāga Recognition System for Indian Art Music

نویسندگان

  • Sankalp Gulati
  • Kaustuv K. Ganguli
  • Swapnil Gupta
  • Ajay Srinivasamurthy
  • Xavier Serra
چکیده

We demonstrate a web-based lightweight real-time melodic analysis and visualization system for Indian art music. Our system uses pitch class profiles, pitch transitions and melodic phrases for melodic characterization and rāga recognition. For each rāga we store a dictionary of its svaras (notes), svara transitions, and typical melodic phrases. We process the input vocals in real-time to estimate pitch, and subsequently perform melody transcription. The likelihood of each rāga is updated in real-time based on the transcribed melody. In order to highlight the melodic events that are characteristic of a rāga, we perform a dynamic visualization of the evolution of the likelihood of all the rāgas for the sung melodic excerpt.

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تاریخ انتشار 2015