Reach Us +44 118 315 0749

Abstract

Detecting tāla Computationally in Polyphonic Context-A Novel Approach

In North-Indian-Music-System (NIMS), tablā is mostly used as percussive accompaniment for vocal-music in polyphonic-compositions. The human auditory system uses perceptual grouping of musical-elements and easily filters the tablā component, thereby decoding prominent rhythmic features like tāla, tempo from a polyphoniccomposition. For Western music, lots of work has been reported for automated drum analysis of polyphoniccomposition. However, attempts at computational analysis of tāla by separating the tablā-signal from mixed signal in NIMS have not been successful. Tablā is played with two components-right and left. The right-hand component has frequency overlap with voice and other instruments. So, tāla analysis of polyphonic-composition, by accurately separating the tablā-signal from the mixture is a baffling task, therefore an area of challenge. In this work we propose a novel technique for successfully detecting tāla using left-tablā signal, producing meaningful results because the left-tablā normally doesn't have frequency overlap with voice and other instruments. North-Indianrhythm follows complex cyclic pattern, against linear appro ach of Western-rhythm. We have exploited this cyclic property along with stressed and non-stressed methods of playing tablā-strokes to extract a characteristic pattern from the left-tablā strokes, which, after matching with the grammar of tāla-system, determines the tāla and tempo of the composition. A large number of polyphonic (vocal+tablā +other-instruments) compositions have been analyzed with the methodology and the result clearly reveals the effectiveness of proposed techniques.


Author(s): Susmita Bhaduri, Anirban Bhaduri and Dipak Ghosh

Abstract | Full-Text | PDF

Share This Article
17+ Million Readerbase
Google Scholar citation report
Citations : 46

American Journal of Computer Science and Information Technology received 46 citations as per Google Scholar report

Abstracted/Indexed in
  • Google Scholar
  • Genamics JournalSeek
  • China National Knowledge Infrastructure (CNKI)
  • CiteFactor
  • Open Academic Journals Index (OAJI)
  • Directory of Research Journal Indexing (DRJI)
  • Jour Informatics
  • CiteSeerx
  • Journal Index.net
  • Secret Search Engine Labs

View More »

Flyer image