Can Musical Emotion Be Quantified With Neural Jitter Or Shimmer? A Novel EEG Based Study With Hindustani Classical Music

TL;DR

This study explores whether neural jitter and shimmer, parameters from speech analysis, can quantify emotional responses to Hindustani classical music using EEG data from participants.

Contribution

It introduces a novel approach of applying speech signal parameters to neural data for emotion recognition in music perception.

Findings

Neural jitter and shimmer vary with emotional content of music.

EEG responses show domain-specific arousal to musical stimuli.

Individual trait characteristics influence neural responses.

Abstract

The term jitter and shimmer has long been used in the domain of speech and acoustic signal analysis as a parameter for speaker identification and other prosodic features. In this study, we look forward to use the same parameters in neural domain to identify and categorize emotional cues in different musical clips. For this, we chose two ragas of Hindustani music which are conventionally known to portray contrast emotions and EEG study was conducted on 5 participants who were made to listen to 3 min clip of these two ragas with sufficient resting period in between. The neural jitter and shimmer components were evaluated for each experimental condition. The results reveal interesting information regarding domain specific arousal of human brain in response to musical stimuli and also regarding trait characteristics of an individual. This novel study can have far reaching conclusions when it comes to modeling of emotional appraisal. The results and implications are discussed in detail.