A PROFILE OF VOCAL AND NON-VOCAL HABITS IN INDIAN LIGHT MUSIC SINGERS - Prakash B. and Shruthi Ravi
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
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
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
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
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
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.