Tabla Gharānā Recognition from Tabla Solo Recordings

Gowriprasad, R and Venkatesh, V and Kodukula, Sri Rama Murty (2022) Tabla Gharānā Recognition from Tabla Solo Recordings. In: 27th National Conference on Communications, NCC 2022, 24 May 2022 through 27 May 2022, Virtual, Online.

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Abstract

Tabla is a percussion instrument in North Indian music tradition. Teaching practices and performances of tabla are based on stylistic schools called gharana-s. Gharana-s are characterized by their unique playing technique, finger posture, improvisations, and compositional patterns (signature patterns). Recognizing the gharana information from a tabla performance is hence helpful to characterize the performance. In this paper, we explore an approach for gharana recognition from solo tabla recordings by searching for the characteristic tabla phrases in these recordings. The tabla phrases are modeled as sequences of strokes, and characteristic phrases from the gharana compositions are chosen as query patterns. The recording is automatically transcribed into a syllable sequence using Hidden Markov Models (HMM). The Rough Longest Common Subsequence (RLCS) approach is used to search for the query pattern instances. A decision rule is proposed to recognize the gharana from the patterns. © 2022 IEEE.

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IITH Creators:

IITH Creators	ORCiD
Kodukula, Sri Rama Murty	https://orcid.org/0000-0002-6355-5287

Item Type:

Conference or Workshop Item (Paper)

Uncontrolled Keywords:

Finger posture; Hidden-Markov models; Improvization; Longest common subsequences; Pattern signature; Percussion instruments; Performance; Playing techniques; Query patterns; Teaching practices

Subjects:

Electrical Engineering

Divisions:

Department of Electrical Engineering

Depositing User:

. LibTrainee 2021

Date Deposited:

02 Aug 2022 11:35

Last Modified:

02 Aug 2022 11:35

URI:

http://raiithold.iith.ac.in/id/eprint/10066