A study on Improvisation in a Musical performance using Multifractal Detrended Cross Correlation Analysis

Sanyal, Shankha; Banerjee, Archi; Patranabis, Anirban; Banerjee, Kaushik; Sengupta, Ranjan; Ghosh, Dipak

doi:10.1016/j.physa.2016.06.013

Cited by 22 publications

(6 citation statements)

References 60 publications

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“…Self-similarity can be measured with Detrended Fluctuation Analysis (DFA) (Peng et al, 1994 ) and its extension Multi-Fractal DFA (MFDFA) (Kantelhardt et al, 2002 ; Oświecimka et al, 2006 ). These methods have been widely used for studying long-range correlations in a broad range of research fields, such as biology (Das et al, 2016 ), economics (Caraiani, 2012 ), music (Sanyal et al, 2016 ), and animal song (Roeske et al, 2018 ). MFDFA can be related to Fourier spectral analysis and both methods provide similar results for the degree of fractality (Heneghan and McDarby, 2000 ).…”

Section: Global Measures Of Variability and Self-similaritymentioning

confidence: 99%

Fractality and Variability in Canonical and Non-Canonical English Fiction and in Non-Fictional Texts

Mohseni

Gast²,

Redies

2021

Front. Psychol.

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This study investigates global properties of three categories of English text: canonical fiction, non-canonical fiction, and non-fictional texts. The central hypothesis of the study is that there are systematic differences with respect to structural design features between canonical and non-canonical fiction, and between fictional and non-fictional texts. To investigate these differences, we compiled a corpus containing texts of the three categories of interest, the Jena Corpus of Expository and Fictional Prose (JEFP Corpus). Two aspects of global structure are investigated, variability and self-similar (fractal) patterns, which reflect long-range correlations along texts. We use four types of basic observations, (i) the frequency of POS-tags per sentence, (ii) sentence length, (iii) lexical diversity, and (iv) the distribution of topic probabilities in segments of texts. These basic observations are grouped into two more general categories, (a) the lower-level properties (i) and (ii), which are observed at the level of the sentence (reflecting linguistic decoding), and (b) the higher-level properties (iii) and (iv), which are observed at the textual level (reflecting comprehension/integration). The observations for each property are transformed into series, which are analyzed in terms of variance and subjected to Multi-Fractal Detrended Fluctuation Analysis (MFDFA), giving rise to three statistics: (i) the degree of fractality () of the fractal spectrum. The statistics thus obtained are compared individually across text categories and jointly fed into a classification model (Support Vector Machine). Our results show that there are in fact differences between the three text categories of interest. In general, lower-level text properties are better discriminators than higher-level text properties. Canonical fictional texts differ from non-canonical ones primarily in terms of variability in lower-level text properties. Fractality seems to be a universal feature of text, slightly more pronounced in non-fictional than in fictional texts. On the basis of our results obtained on the basis of corpus data we point out some avenues for future research leading toward a more comprehensive analysis of textual aesthetics, e.g., using experimental methodologies.

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Section: Global Measures Of Variability and Self-similaritymentioning

confidence: 99%

Fractality and Variability in Canonical and Non-Canonical English Fiction and in Non-Fictional Texts

Mohseni

Gast²,

Redies

2021

Front. Psychol.

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“…Detrended Fluctuation Analysis (DFA) (Peng et al, 1994) and its extension Multi-Fractal DFA (MFDFA) (Kantelhardt et al, 2002) have been widely used in studying long-range correlations in a broad range of research fields, such as biology (Das et al, 2016), economics (Caraiani, 2012), music (Sanyal et al, 2016) and animal song (Roeske et al, 2018). MFDFA can be related to Fourier spectral analysis and both methods provide similar results for the degree of fractality (Heneghan and McDarby, 2000).…”

Section: Detrended Fluctuation Analysismentioning

confidence: 99%

Comparative Computational Analysis of Global Structure in Canonical, Non-Canonical and Non-Literary Texts

Mohseni,

Gast,

Redies

2020

Preprint

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This study investigates global properties of literary and non-literary texts. Within the literary texts, a distinction is made between canonical and non-canonical works. The central hypothesis of the study is that the three text types (non-literary, literary/canonical and literary/non-canonical) exhibit systematic differences with respect to structural design features as correlates of aesthetic responses in readers. To investigate these differences, we compiled a corpus containing texts of the three categories of interest, the Jena Textual Aesthetics Corpus. Two aspects of global structure are investigated, variability and self-similar (fractal) patterns, which reflect long-range correlations along texts. We use four types of basic observations, (i) the frequency of POS-tags per sentence, (ii) sentence length, (iii) lexical diversity in chunks of text, and (iv) the distribution of topic probabilities in chunks of texts. These basic observations are grouped into two more general categories, (a) the low-level properties (i) and (ii), which are observed at the level of the sentence (reflecting linguistic decoding), and (b) the high-level properties (iii) and (iv), which are observed at the textual level (reflecting comprehension). The basic observations are transformed into time series, and these time series are subject to multifractal detrended fluctuation analysis (MFDFA), giving rise to three statistics: (i) the degree of fractality, (ii) the fractal dimension (width of the fractal spectrum), and (iii) the degree of asymmetry of the fractal spectrum. Our results show that low-level properties of texts are better discriminators than high-level properties, for the three text types under analysis. Canonical literary texts differ from non-canonical ones primarily in terms of variability. Fractality seems to be a universal feature of text, more pronounced in non-literary than in literary texts. While some of our results are hard to interpret from a literary point of view, we surmise that our findings reflect an important design feature of text, the distribution of discourse modes (Narrative, Report, Description, Information, Argument). Beyond the specific results of the study, we intend to open up new perspectives on the experimental study of textual aesthetics.

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“…MFDFA has been applied successfully to study multi-fractal scaling behavior of various non-stationary time series [51][52][53] as well as in detection or prognosis of diseases [54,55], scaling of music signals [55]. The multi-fractal s are fundamentally more complex and inhomogeneous than mono-fractals [56] and describe time series featured by very irregular dynamics, with sudden and intense bursts of high-frequency fluctuations [57].…”

Section: Archivos De Medicina Issn 1698-9465 Journal Of Neurology Andmentioning

confidence: 99%

Universality and Domain Specificity of Emotion-A Quantitative Non Linear EEG Based Approach

Banerjee¹,

Sanyal²,

Sengupta³

et al. 2017

J Neurol Neurosci

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Music has been present in human culture since time immemorial, some say music came even before speech. The effort to understand the wide variety of emotions evoked by music has started not long back. With the advent and rapid growth of various neurological bio-sensors we can now attempt to quantify various dimensions of emotional experience induced by music especially instrumental music -since it is free from any language barriers. In this study, we took eight (8) cross cultural instrumental clips originating mainly from Indian and Western music. A listening test comprising of 100 participants across the globe was conducted to associate each clip with its corresponding emotional valence. The participants were asked to mark each clip according to their perception of four basic emotions (joy/sorrow and anxiety/serenity) invoked by each instrumental clip. EEG study was then conducted on 10 participants to measure the response evoked by the same instrumental clips in the alpha and theta frequency regions. We took the help of latest non-linear multi-fractal analysis technique -MFDFA to estimate the change in multi-fractal spectral width (corresponding to alpha as well as theta waves) associated with each of the clips in frontal, temporal and occipital lobes. The response in the alpha domain reveals a hint in the direction of universality of music, while in theta domain we have culture specific response. Moreover, we tried to develop alpha as well as theta multi-fractal spectral width as a single parameter with which we can quantify the valence and arousal based effects corresponding to a particular musical clip. The results and implications are discussed in detail.

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A study on Improvisation in a Musical performance using Multifractal Detrended Cross Correlation Analysis

Cited by 22 publications

References 60 publications

Fractality and Variability in Canonical and Non-Canonical English Fiction and in Non-Fictional Texts

Fractality and Variability in Canonical and Non-Canonical English Fiction and in Non-Fictional Texts

Comparative Computational Analysis of Global Structure in Canonical, Non-Canonical and Non-Literary Texts

Universality and Domain Specificity of Emotion-A Quantitative Non Linear EEG Based Approach

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