Understanding and Classifying Cultural Music Using Melodic Features Case Of Hindustani, Carnatic And Turkish Music

06/21/2019
by   Amruta Vidwans, et al.
0

We present a melody based classification of musical styles by exploiting the pitch and energy based characteristics derived from the audio signal. Three prominent musical styles were chosen which have improvisation as integral part with similar melodic principles, theme, and structure of concerts namely, Hindustani, Carnatic and Turkish music. Listeners of one or more of these genres can discriminate between these based on the melodic contour alone. Listening tests were carried out using melodic attributes alone, on similar melodic pieces with respect to raga/makam, and removing any instrumentation cue to validate our hypothesis that style distinction is evident in the melody. Our method is based on finding a set of highly discriminatory features, derived from musicology, to capture distinct characteristics of the melodic contour. Behavior in terms of transitions of the pitch contour, the presence of micro-tonal notes and the nature of variations in the vocal energy are exploited. The automatically classified style labels are found to correlate well with subjective listening judgments. This was verified by using statistical tests to compare the labels from subjective and objective judgments. The melody based features, when combined with timbre based features, were seen to improve the classification performance.

READ FULL TEXT

page 5

page 16

research
11/10/2020

Deconstruct and Reconstruct Dizi Music of the Northern School and the Southern School

Today's research on Chinese music technology is mainly focused on three ...
research
06/17/2014

Automatic Fado Music Classification

In late 2011, Fado was elevated to the oral and intangible heritage of h...
research
02/09/2021

TräumerAI: Dreaming Music with StyleGAN

The goal of this paper to generate a visually appealing video that respo...
research
08/05/2021

Performer Identification From Symbolic Representation of Music Using Statistical Models

Music Performers have their own idiosyncratic way of interpreting a musi...
research
11/09/2019

Beyond Statistical Relations: Integrating Knowledge Relations into Style Correlations for Multi-Label Music Style Classification

Automatically labeling multiple styles for every song is a comprehensive...
research
08/04/2020

Music SketchNet: Controllable Music Generation via Factorized Representations of Pitch and Rhythm

Drawing an analogy with automatic image completion systems, we propose M...
research
08/23/2018

Review-Driven Multi-Label Music Style Classification by Exploiting Style Correlations

This paper explores a new natural language processing task, review-drive...

Please sign up or login with your details

Forgot password? Click here to reset