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