Cohen Courses:Learning Indian Classical Using Sequential Models

Team Members

• Dhananjay Kulkarni
• Tarun Kumar

Project Idea

Indian Classical music is a very structured when it comes to melody. A composition is (generally) within a constraints of a raag. It has a specific grammar, which lends the emotions to the composition. This aspect of music lends an interesting application of sequential models for note prediction, and raga classification.

Problem Statement

Pakad

Pakad is a string of notes characteristic to a Raga to which a musician frequently returns while improvising in a performance. A pakad has the potential to illustrate the grammar and aesthetics of a raga. For example consider raga Bageshree. The pakad is F G A F D# D C. It can be rendered in various ways as -

• F G A F D# F DC
• F G A F G D# F D C
• F G A , D# F D C

The following are valid sequences in Bageshree, but they are not pakads -

• F G A G F D# D C
• F A G F D# F D C

Baseline

In [2], the pakad matching was done using $\delta$-Occurence with $\alpha$-Bounded Gaps. This however, fails for the two sequences displayed above.

Grand Idea

The grand idea is to view this task as a sequence alignment problem. There has been considerable work in machine translation. The challenge would be to adapt this work.

Dataset

There are midi files available at http://www.cse.iitk.ac.in/users/tvp/music/. These will be manually annotated for pakads.

References

1. http://www.slideshare.net/butest/music-and-machine-learning

2. TANSEN : A SYSTEM FOR AUTOMATIC RAGA IDENTIFICATION