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The Acoustical Character of Sounds from Indian Twin Drums
... pecially the dayan are an exception. This was pointed out as early as 1920 by C. V. Raman and S. Kumar. Raman further refined the study in a later paper (Ghosh R N, 1922, Raman C V, 1934, Rao K N, 1938. Thereafter several theoretical and experimental studies were held on the dynamics of the instrument (Ramakrishna B S, 1957, Sarojini T et. al, 1958, Banerjee B M et. al, 1991, Courtney D, 1999). The classical model put forth by Raman represents the sound of tabla-dayan, as having a spectrum consisting of five harmonics; these are the fundamental with its four overtones (Courtney D, 1999). Here we studied the timbre characteristics of tabla strokes. ...
Indian twin drums mainly bayan and dayan (tabla) are the most important
percussion instruments in India popularly used for keeping rhythm. It is a twin
percussion/drum instrument of which the right hand drum is called dayan and the
left hand drum is called bayan. Tabla strokes are commonly called as `bol',
constitutes a series of syllables. In this study we have studied the timbre
characteristics of nine strokes from each of five different tablas. Timbre
parameters were calculated from LTAS of each stroke signals. Study of timbre
characteristics is one of the most important deterministic approach for
analyzing tabla and its stroke characteristics. Statistical correlations among
timbre parameters were measured and also through factor analysis we get to know
about the parameters of timbre analysis which are closely related. Tabla
strokes have unique harmonic and timbral characteristics at mid frequency range
and have no uniqueness at low frequency ranges.
... Diese Ergebnisse finden sich auch bei Fletcher und Rossing (1998). Banerjee und Nag (1991) haben Tablaklänge analysiert und 3D-Spektren angegeben. Hinweise auf neuere Untersuchungen und Unterrichtsbücher zur Tabla finden sich auf "The Tabla Site" im Internet (Courtney 2002). ...
INVESTIGATIONS ON THE VIBRATION AND SOUND OF THE INDIAN TABLA
The tabla pair is a centuries old musical instrument from North India consisting of two different drums. The bigger one, played by the left hand, is called a bayan, the smaller one, played by the right hand, is named tabla. Mechanical vibration patterns of the drum heads are selectively evoked and suppressed according to the traditional striking and fingering techniques. The aim of the study is to investigate the relationship between these vibrations on the one hand and the acoustic signal on the other hand. Several characteristic strokes were played by two professional players and recorded on DAT for further analysis. In parallel, the mechanical vibrations of the drum heads of one of these tabla pairs were measured by excitation via a loudspeaker using Laser Doppler vibrometry. This technique allowed the operating deflection shapes of the tabla and bayan heads to be ascertained.
All acoustic signals were also investigated by Fast Fourier transformation (sound level spectrum as a function of time in waterfall representation) and by an aurally-related approach. The latter one used the commercially available software VIPER, which includes aurally-adequate frequency analysis, frequency contouring and spectral masking. The most advanced stage of processing were “frequency tracks”. By considering spectral masking, the physical information was reduced to its aurally-relevant content. This representation also proved to be suited to the interpretation of the tabla and bayan sounds in terms of vibrational modes. For the masked frequency tracks of the tonal tabla strokes, tun and na as examples, the aurally-relevant partial tones were interrelated to the corresponding vibrations. Knowledge of the vibrational patterns is the key for the physical understanding of the striking and fingering technique.
This chapter deals with analysis of musical instruments especially the Indian musical instruments by analyzing its sound. Sections 9.1, 9.2 and 9.3 concerns the automatic recognition of musical instruments with the idea that extract the perceptually relevant features from acoustic musical signals that a computer system “listen” to musical sounds and recognize which instrument is playing. For this, timbre of the sound of those musical instruments needs to be studied extensively. Only five musical instruments which are popularly adopted in Hindustani music were chosen for study.
We investigate the effects of air loading on the acoustical properties of tabla, an Indian musical drum, by idealizing it as a composite membrane backed by a rigid cylindrical cavity. The coupled boundary value problem for membrane vibration and acoustic pressure, assuming acoustic radiations to be the only source of dissipation, is solved using a Green's function method. We show that air loading helps in only fine tuning of the harmonicity of the composite membrane in the right hand tabla, but significantly improves the harmonicity in the left hand tabla. In both the cases, it increases the decay time of the musically important modes. With a suitably defined error as the objective function, we find optimum tabla designs which yield the most harmonic frequency spectrum. The obtained results are found to be consistent with the actual design of the tabla. We have also attempted modal sound synthesis of the percussion instrument.
Tabla, a percussion instrument, mainly used to accompany vocalists,
instrumentalists and dancers in every style of music from classical to light in
India, mainly used for keeping rhythm. This percussion instrument consists of
two drums played by two hands, structurally different and produces different
harmonic sounds. Earlier work has done labeling tabla strokes from real time
performances by testing neural networks and tree based classification methods.
The current work extends previous work by C. V. Raman and S. Kumar in 1920 on
spectrum modeling of tabla strokes. In this paper we have studied spectral
characteristics (by wavelet analysis by sub band coding method and using
torrence wavelet tool) of nine strokes from each of five tablas using Wavelet
transform. Wavelet analysis is now a common tool for analyzing localized
variations of power within a time series and to find the frequency distribution
in time frequency space. Statistically, we will look into the patterns depicted
by harmonics of different sub bands and the tablas. Distribution of dominant
frequencies at different sub-band of stroke signals, distribution of power and
behavior of harmonics are the important features, leads to categorization of
tabla.
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