Signal Analysis of Hindustani Classical Music

Datta, Asoke Kumar; Solanki, Sandeep Singh; Sengupta, Ranjan; Mahto, Kartik; Patranabis, Anirban

doi:10.1007/978-981-10-3959-1

Cited by 22 publications

(8 citation statements)

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“…Remark: Readers interested in further literature in Indian music and scientific research therein are referred to [12], [13] and [14].…”

Section: Discussionmentioning

confidence: 99%

A Comparative Statistical Analysis of Two Popular Indian Patriotic Songs

Rahman¹

2021

JAMC

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Pressing the keys of a piano randomly does not create music. Music is created only when there is a pattern in the musical notes. This pattern gets embedded in the corresponding musical data, numerical in character. Given that statistics is the science of exploring and studying patterns in numerical data, we are motivated to perform a statistical analysis, with special emphasis on modeling wherein lies the strength of statistics, of one of India's patriotic songs 'Aye Mere Watan Ke Logo'.There is also a comparative study done with India's National Anthem Jana Gana Mana. The experimental results are quite interesting. Scatter plot plotted between these two patriotic songs shows that the two songs are entirely different from each other. Apart from modeling, there are other comparative studies done through Information Content and Box plot. For India's National Anthem, note A has the highest Information content of 4.7116. In case of 'Aye Mere Watan Ke Logo', note E has the highest Information content of 6.0371. The note E has the highest probability for India's National Anthem as compared to the note G for Aye Mere Watan Ke Logo. From Box plot we get that India's National Anthem is positively skewed whereas Aye Mere Watan Ke Logo is approximately symmetric. But it is quite interesting to note that, despite the aforesaid differences, both the songs can be approximated by the same time series model to a fair degree of accuracy.

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“…Remark: Readers interested in further literature in Indian music and scientific research therein are referred to [12], [13] and [14].…”

Section: Discussionmentioning

confidence: 99%

A Comparative Statistical Analysis of Two Popular Indian Patriotic Songs

Rahman¹

2021

JAMC

Self Cite

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“…Svara (swara) in Sanskrit connotes a specific breath, vowel, and corresponding musical note. This ancient Indian concept of musical pitch is thoroughgoingly symbolic, so much so, that melodies become words, and poetry can be expressed instrumentally (Datta et al 2017). Poetry, of Tagore, say read in diverse contexts must be reinterpreted, and often are instrumentally (without the lyrics) interpreting the poem for the present location (Desha), circumstances (Kaala) and impetus that triggered the emotion eliciting the poem (Karana).…”

Section: Section 3: Language and Music Overlapping In Humansmentioning

confidence: 99%

The Musical Turn in Biosemiotics: An Expressivist Model of Communication

Slayton

Hendlin

2022

Preprint

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Human music and language are two systems of communication and expression that, while historically considered to overlap, have become increasingly divergent in their approach and study. Music and language almost certainly co-evolved and emerged from the same semiotic field, and this relationship as well as co-origin are actively researched and debated. For the sake of evaluating the semiotic content of zoomusicology, we investigate music from a ‘bottom-up’ biosemiotic functionalist account considering iconic, indexical, and symbolic forms of meaning not in a hierarchy but according to their effects on agents. Such an approach avoids overintellectualizing the representational aspects of music, and instead inverts, as it were, the traditional hierarchy of semiotic categories to produce illocutionary effects. Understanding aesthetics and action not as a priori separate but rather fundamentally co-arising elements of the same events, the focus of musicality again returns to interpretation and how semiosis precipitates expression.

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“…It is expected that during voice mutation, changes in timbre are noticeable. The tristimulus assesses the amplitude of the fundamental (a 1 ), of the sum of the second (a 2 ), third (a 3 ) and fourth (a 4 ) partials, and in the sum of partials higher than the fourth in relation to the aggregate amplitude of the established part of the signal [17]:…”

Section: Voice Features Extractionmentioning

confidence: 99%

Adolescent age estimation using voice features

Bugdoł

Bugdol

Bieńkowska

et al. 2020

Biomedical Engineering / Biomedizinische Technik

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In this paper, a method for evaluating the chronological age of adolescents on the basis of their voice signal is presented. For every examined child, the vowels a, e, i, o and u were recorded in extended phonation. Sixty voice parameters were extracted from each recording. Voice recordings were supplemented with height measurement in order to check if it could improve the accuracy of the proposed solution. Predictor selection was performed using the LASSO (least absolute shrinkage and selection operator) algorithm. For age estimation, the random forest (RF) for regression method was employed and it was tested using a 10-fold cross-validation. The lowest absolute error (0.37 year ± 0.28) was obtained for boys only when all selected features were included into prediction. In all cases, the achieved accuracy was higher for boys than for girls, which results from the fact that the change of voice with age is larger for men than for women. The achieved results suggest that the presented approach can be employed for accurate age estimation during rapid development in children.

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Signal Analysis of Hindustani Classical Music

Cited by 22 publications

References 0 publications

A Comparative Statistical Analysis of Two Popular Indian Patriotic Songs

A Comparative Statistical Analysis of Two Popular Indian Patriotic Songs

The Musical Turn in Biosemiotics: An Expressivist Model of Communication

Adolescent age estimation using voice features

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