Computational Archiving and EEG-Based Analysis of Carnatic Music

Computational Aspects of Classical Music

Objective

• The objective of this work is to study and archive carnatic music using a computational approach. Appropriate signal processing algorithms will be used to classify the quality of recording and analyse them for meta information. The effect of music on health will also be studied.

Description

• Use a composition segmentation tool, raga recognition app, concert segmenter, and stroke recognition system to determine, segment and transcribe various features of carnatic music, Design and develop a low cost EEG system to articulate the signatures (corresponding to different types of music stimuli) found in the EEG using text to speech synthesis systems in vernacular languages.

Impact

• Novel signal processing and machine learning algorithms developed under CompMusic will enable better navigation and perform a motivic analysis of the huge repository of Carnatic music that is available on websites like Sangeethapriya.org, rasikas.org, youtube. The effect of different types of ragas on human state of mind, particularly for those with speech difficulties, can be actualized using EEG and text to speech synthesis systems.