| Ninād, Journal of the ITC-SRA, vol.19
December 2005: Abstracts
A PROFILE OF VOCAL AND NON-VOCAL HABITS IN INDIAN LIGHT MUSIC SINGERS
- Prakash B. and Shruthi Ravi
Abstract
Vocal and non-vocal habits play a vital role in the life and career of
singers. Yet, most singers have a vague awareness of the same, due to
which vocal misuses and abuses are often present as the primary cause of
their vocal difficulties. A questionnaire of thirty questions was
developed to collect information regarding practices and methods of
training and non-vocal habits of Indian light music singers (27
subjects, 19 females and 8 males) in Chennai City. The data collected
was subjected to a statistical analysis and the results profiled the
vocal and non-vocal habits of the subjects. The discussion focussed on
the possible influences of the practices, work culture and non-vocal
habits on the singing voice and the outlook of the singer towards their
profession.
A PSYCHO-PERCEPTUAL HYPOTHESIS FOR SHRUTIS IN INDIAN MUSIC - K. Datta,
R. Sengupta, N. Dey, D. Nag and A. Mukerjee
Abstract
The Indian musical scale is based on shrutis. The ancient definition of
shruti is used along with the psycho-perceptual processes of hearing and
an assumption of overall uniform distribution of the shrutis over the
octave. The hypothesis gives maximum number of shrutis as 66 conforming
to some ancient literature. A process of selection of subsets on the
basis of defined better acceptability and different iterations of
pruning algorithm gives the numbers 53 and 22 which are also mentioned
in ancient literature. The shrutis thus obtained show good conformity
with some of the scales available in literature.
BEYOND SWAYAMBHU GANDHAR : AN ANALYSIS OF PERCEIVED TANPURA NOTES -
Paritosh K. Pandya
Abstract
Tanpura sound has rich harmonic structure leading to the perception of
several perceived notes for which there are no corresponding tuned
strings. We analyse the spectrogram of tanpura to find harmonic partials
which correlate well with the perception of these "swayambhu" notes.
From this analysis, we determine the exact shrutis of the perceived
tanpura notes.
NADIA TU DHIRE BAHO RE : FILM SOUNDTRACK AS A MUSICAL PORTRAIT -
Amelia Maciszewski
Abstract
This article examines a documentary film made on Girija Devi, exploring
the reasons that prompted its making, the format used and the music that
was incorporated into the film's sound track, thus bringing out the
essence of the artiste's personality.
PRE-REQUISITES OF INDIAN MELODIES - R. K. Das
Abstract
Many authoritative practising musicians and music
scholars declare that India's raga music is 6000 years old and it
originated from the sacred Veda. But, the ragas are believed to have
derived from gram, murchhana and jati, yet rarely does a musician
correlate the ragas with them. In this article the author tries to
establish the connections between the old and the new concepts of
melodies by interpreting a shuddha jati in the present system of ragas
and notation.
SEGMENTATION AND RECOGNITION OF TABLA STROKES - Parag Chordia
Abstract
A system that segments and labels tabla strokes from real performances
is described. Performance is evaluated on a large database taken from
three performers under different recording conditions, containing a
total of 16,834 strokes. The current work extends previous work by
citepgillet on categorizing tabla strokes, by using a larger, more
diverse database that includes their data as a benchmark, and by testing
neural networks and tree-based classication methods. First, the
time-domain signal was segmented using complex-domain thresholding that
looked for sudden changes in amplitude and phase discontinuities. At the
optimal point on the ROC curve, false positives were less than 1% and
false negatives were less than 2%. Then, classication was performed
using a multivariate Gaussian model (mv gauss) as well as non-parametric
techniques such as probabilistic neural networks (pnn), feedforward
neural networks (ffnn), and tree-based classiers. Two evaluation
protocols were used. The first used 10-fold cross validation. The
recognition rate averaged over several experiments that contained 10-15
classes was 92% for the mv gauss, 94% for the ffnn and pnn, and 84% for
the tree based classifier. To test generalization, a more difficult
independent evaluation was undertaken in which no test strokes came from
the same recording as the training strokes. The average recognition rate
over a wide variety of test conditions was 76% for the mv gauss, 83% for
the ffnn, 76% for the pnn, and 66% for the tree classifier.
Mail us
your request
Top Back to Publication
Page
|