Detecting T¯Ala Computationally in Polyphonic Context - a Novel Approach

Detecting t¯ala Computationally in Polyphonic Context - A Novel Approach Susmita Bhaduri1, Anirban Bhaduri2, Dipak Ghosh3 1;2;3Deepa Ghosh Research Foundation, Kolkata-700031,India [email protected] [email protected] [email protected] Abstract the left-tabl¯a strokes, which, after matching with the grammar of t¯ala-system, determines the t¯ala and tempo of the composition. A large number of In North-Indian-Music-System(NIMS),tabl¯a is polyphonic(vocal+tabl¯a+other-instruments) com- mostly used as percussive accompaniment for positions has been analyzed with the methodology vocal-music in polyphonic-compositions. The hu- and the result clearly reveals the effectiveness of man auditory system uses perceptual grouping of proposed techniques. musical-elements and easily filters the tabl¯a compo- Keywords:Left-tabl¯a drum , T¯ala detection, nent, thereby decoding prominent rhythmic features Tempo detection, Polyphonic composition, Cyclic like t¯ala, tempo from a polyphonic-composition. For pattern, North Indian Music System Western music, lots of work have been reported for automated drum analysis of polyphonic-composition. However, attempts at computational analysis of t¯ala 1 Introduction by separating the tabl¯a-signal from mixed signal in NIMS have not been successful. Tabl¯a is Current research in Music-Information- played with two components - right and left. The Retrieval(MIR) is largely limited to Western right-hand component has frequency overlap with music cultures and it does not address the North- voice and other instruments. So, t¯ala analysis of Indian-Music-System hereafter NIMS, cultures in polyphonic-composition, by accurately separating general. NIMS raises a big challenge to current the tabl¯a-signal from the mixture is a baffling task, rhythm analysis techniques, with a significantly arXiv:1611.05182v2 [cs.SD] 24 Sep 2018 therefore an area of challenge. In this work we sophisticated rhythmic framework. We should propose a novel technique for successfully detecting consider a knowledge-based approach to create the t¯ala using left-tabl¯a signal, producing meaningful computational model for NIMS rhythm. Tools results because the left-tabl¯a normally doesn't have developed for rhythm analysis can be useful in a frequency overlap with voice and other instruments. lot of applications such as intelligent music archival, North-Indian-rhythm follows complex cyclic pattern, enhanced navigation through music collections, against linear approach of Western-rhythm. We content based music retrieval, for an enriched and have exploited this cyclic property along with informed appreciation of the subtleties of music stressed and non-stressed methods of playing tabl¯a- and for pedagogy. Most of these applications deal strokes to extract a characteristic pattern from with music compositions of polyphonic kind in the 1 context of blending of various signals arising from from polyphonic composition having tabl¯a as one of different sources. Apart from the singing voice, the percussive instruments, may be to extract the different instruments are also included. tabl¯a signal from it and analyze it separately. The As per [1] rhythm relates to the patterns of dura- dayan has a frequency overlap with other instruments tion that are phenomenally present in the music. It and mostly human-voice for polyphonic music, so if should be noted that that these patterns of duration we extract the whole range of frequencies for both are not based on the actual duration of each musical bayan and dayan components, by existing frequency event but on the Inter Onset Interval(IOI) between based filtering methods, the resultant signal will be the attack points of successive events. As per[ [2]], an a noisy version of original song as it will still have accent or a stimulus is marked for consciousness in part of other instruments, human voice components some way. Accents may be phenomenal, i.e. changes along with tabl¯a. Also conventional source separa- in intensity or changes in register, timbre, duration, tion methods lead to substantial loss of information or simultaneous note density or structural like ar- or sometimes addition of unwanted noise. This is rival or departure of a cadence which causes a note the an area of challenge in t¯ala analysis for NIMS. to be perceived as accented. It may be metrical ac- Although, NIMS t¯ala functions in many ways like cent which is perceived as accented due to its metri- Western meter, as a periodic, hierarchic framework cal position[ [3]. Percussion instruments are normally for rhythmic design, it is composed of a sequence of used to create accents in the rhythmic composition. unequal time intervals and has longer time cycles. The percussion family which normally includes tim- Moreover t¯ala in NIMS is distinctively cyclical and pani, snare drum, bass drum, cymbals, triangle, is much more complex compared to Western meter[ [7]]. believed to include the oldest musical instruments, This complexity is another challenge for t¯ala analysis. following the human voice[ [4]]. The rhythm infor- Due to the above reasons defining a computa- mation in music is mainly and popularly provided tional framework for automatic rhythm information by the percussion instruments. One simple way of retrieval for North Indian polyphonic compositions analyzing rhythm of a composite or polyphonic mu- is a challenging task. Very less work has been done sic signal having some percussive component, may for rhythmic information retrieval from a polyphonic be to extract the percussive component from it us- composition in NIMS context. In Western music, ing some source separation techniques based on fre- quite a few approaches are followed for this purpose, quency based filtering. Various attempts have been mostly in the areas of beat-tracking, tempo analysis, made in Western music to develop applications for annotation of strokes/pulses from the separated per- re-synthesizing the drum track of a composite mu- cussive signal. We have described these systems in sic signal, identification of type of drums played in the Section 3. For NIMS, very few works of rhythm the composite signal[ex. the works of [5, 6] etc., de- analysis are done by adopting Western drum-event scribed in Section 3 in detail]. Human listeners are retrieval system. These works result in finding out able to perceive individual sound events in complex meter or speed which are not very significant in the compositions, even while listening to a polyphonic context of NIMS. Hence this is an unexplored area of music recording, which might include unknown tim- research for NIMS. bres or musical instruments. However designing an In this work we have proposed a completely new automated system for rhythm detection from a poly- approach, i.e.instead of extracting both bayan and phonic music composition is very difficult. dayan signal, we have extracted the bayan signal from In the context of NIMS rhythm popularly known as the polyphonic composition by using band-pass filter. t¯ala, tabl¯a is the most popular percussive instrument. This filter extracts lower frequency part which nor- Its right hand drum-dayan and left hand drum-bayan mally does not overlap with the frequency of human are played together and amplitude-peaks spaced at voice and other instruments in a polyphonic compo- regular time intervals, are created by playing every sition. Most of the t¯ala-s start with a bol or stroke stroke. One way of rhythm information retrieval which has a bayan component(either played with 2 bayan alone or both bayan and dayan together) and also the some consequent section(vibh¯aga in NIMS terminology) boundary-bol-s have similar bayan component. Hence these strokes would be captured in the extracted bayan signal. For a polyphonic composition, its t¯ala is rendered with cyclically recurring patterns of fixed time-lengths. This is the cyclic property of NIMS, discussed in detail in section 2. So after extracting the starting bol-s and the section boundary strokes from the bayan signal, we can exploit the cyclic property of a t¯ala and the pattern of strokes appearing in a single cycle and can detect important rhythm information from a polyphonic composition. This would be a positive step towards rhythm information retrieval from huge collection of music record- ings for both film music and live performances of various genres of hindi music. Here, we consider the t¯ala detection of different single-channel, polyphonic clips of hindi vocal songs of devotional, semi-classical and movie soundtracks from NIMS, having variety of tempo and m¯atr¯a-s. Figure 1: The hierarchy of NIMS t¯ala illustrated with The rest of the paper is organized as follows. A jhaptal review of past work is presented in section 3. Some definitions are provided in section 2. In section 4 the proposed methodology is elaborated. Experimental • M¯atra: The overall time-span of each cycle or results are placed in section 5 and the paper ends ¯avart is made up of a certain number of smaller with concluding remarks in section 6. time units called m¯atra-s. The number of m¯atra- s for the NIMS t¯ala-s, usually varies from 6 to 16. 2 Definitions • Vibh¯aga: The m¯atra-s of a t¯ala are grouped 2.1 T¯ala and its structure in NIMS into sections, sometimes with unequal time- spans, called vibh¯aga-s. The basic identifying features of rhythm or t¯ala in • Bol: In the t¯ala system of North Indian mu- NIMS are described as follows. sic, the actual articulation of t¯ala is done by • T¯ala and its cyclicity: North Indian music is metrically organized and it is called ni- baddh(bound by rhythm) music. This kind of music is set to a metric framework called t¯ala.

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