Multifractal Detrended Cross-Correlation Analysis for Characterization of Spoken Language – A New Method to explore the Genesis of Languages
DOI:
https://doi.org/10.52783/jns.v14.2100Keywords:
Indian Languages, MFDFA, MFDXA, Cross-Correlation, Language Genesis, ANOVA, Mahalanobis DistanceAbstract
This work presents a novel use of chaos-based non-linear techniques coupled with statistical methods for spoken language characterization in the speech signal domain. Our goal is to create a framework that highlights linguistic commonalities. While Multifractal Detrended Cross-Correlation Analysis (MFDXA) assesses long-term cross-correlations between languages using the cross-correlation coefficient as a measure of similarity, Multifractal Detrended Fluctuation Analysis (MF-DFA) is used to examine linguistic correlations among the languages.
Bengali, Assamese, Maithili, Odia, Nepali, Manipuri, Hindi, Urdu, Marathi, Gujarati, Punjabi, Konkani, Tamil, Telugu, Malayalam, Kannada, and Sanskrit are among the seventeen Indian languages that are the emphasis of the present work. The speech corpus, which includes speakers of both sexes, is mostly composed of unplanned conversational material on a variety of subjects, including social welfare, agriculture, and in-person interviews. This model is unique in that it avoids the conventional use of linguistic information. Our findings reveal notable deviations from established linguistic theories in cases such as Bengali-Gujarati, Hindi-Tamil, and Bengali-Kannada, indicating that current language classifications may benefit from re-evaluation. Statistical tools like ANOVA and Mahalanobis Distance have been used to validate the current study. The proposed method offers a valuable approach to investigating the origins of languages within a global framework
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Academi, K. S. KERALA SAHITYA AKADEMI. http://www.keralasahityaakademi.org/
Ashkenazy, Y., Baker, D. R., Gildor, H., & Havlin, S. (2003). Nonlinearity and multifractality of climate change in the past 420,000 years. Geophysical research letters, 30(22).
Berument, M. H., Ceylan, N. B., & Dogan, N. (2010). The impact of oil price shocks on the economic growth of selected MENA1 countries. The Energy Journal, 31(1), 149-176.
Bradlow, A., Clopper, C., Smiljanic, R., & Walter, M. A. (2010). A perceptual phonetic similarity space for languages: Evidence from five native language listener groups. Speech communication, 52(11-12), 930-942.
C. M. Jones, G. K. (1996). Oil and the Stock Markets. The Journal of Finance, 915-932. https://doi.org/ https://doi.org/10.1111/j.1540-6261.1996.tb02691.x
Chen, S.-S. (2009). Oil price pass-through into inflation. Energy economics, 31(1), 126-133.
DC González, L. L. L., F Violaro. (2012). Analysis of the multifractal nature of speech signals. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 17th Iberoamerican Congress, CIARP 2012, Buenos Aires, Argentina.
Deb, D. (2012). On case marking in assamese bengali and oriya. International Journal of Applied Linguistics & English Literature, 1(2), 102.
Downey, S. S., Hallmark, B., Cox, M. P., Norquest, P., & Lansing, J. S. (2008). Computational feature-sensitive reconstruction of language relationships: Developing the ALINE distance for comparative historical linguistic reconstruction. Journal of Quantitative Linguistics, 15(4), 340-369.
Dutt, S. (2013). India in a globalized world. In India in a globalized world. Manchester University Press.
George Cardona, D. J. (2007). The Indo-Aryan Languages. Routledge, London.
Ghosh, D., Dutta, S., & Chakraborty, S. (2014). Multifractal detrended cross-correlation analysis for epileptic patient in seizure and seizure free status. Chaos, Solitons & Fractals, 67, 1-10.
He, L.-Y., & Chen, S.-P. (2011). Multifractal detrended cross-correlation analysis of agricultural futures markets. Chaos, Solitons & Fractals, 44(6), 355-361.
Hedayatifar, L., Vahabi, M., & Jafari, G. (2011). Coupling detrended fluctuation analysis for analyzing coupled nonstationary signals. Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 84(2), 021138.
Horvatic, D., Stanley, H. E., & Podobnik, B. (2011). Detrended cross-correlation analysis for non-stationary time series with periodic trends. Europhysics Letters, 94(1), 18007.
Jain, D., & Cardona, G. (2007). The Indo-Aryan Languages. Routledge.
Jiang, Z.-Q., & Zhou, W.-X. (2011). Multifractal detrending moving-average cross-correlation analysis. Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 84(1), 016106.
Kantelhardt, J. W., Zschiegner, S. A., Koscielny-Bunde, E., Havlin, S., Bunde, A., & Stanley, H. E. (2002). Multifractal detrended fluctuation analysis of nonstationary time series. Physica A: Statistical Mechanics and its Applications, 316(1-4), 87-114.
Kettunen, K., Sadeniemi, M., Lindh-Knuutila, T., & Honkela, T. (2006). Analysis of EU languages through text compression. International Conference on Natural Language Processing (in Finland),
Khadabadi, B., & Akādamī, P. t. B. (1997). Studies in Jainology, Prakrit literature, and languages: a collection of select 51 papers. (No Title).
Kolipakam, V., Jordan, F. M., Dunn, M., Greenhill, S. J., Bouckaert, R., Gray, R. D., & Verkerk, A. (2018). A Bayesian phylogenetic study of the Dravidian language family. Royal Society open science, 5(3), 171504.
Kondrak, G. (2000). A new algorithm for the alignment of phonetic sequences. 1st Meeting of the North American Chapter of the Association for Computational Linguistics,
Krishnamurti, B. (2006). The Dravidian languages (1st ed.). Cambridge University Press.
McMahon, A., & McMahon, R. (2005). Language classification by numbers. Oxford University Press.
Movahed, M. S., & Hermanis, E. (2008). Fractal analysis of river flow fluctuations. Physica A: Statistical Mechanics and its Applications, 387(4), 915-932.
Oco, N., Syliongka, L. R., Roxas, R. E., & Ilao, J. (2013). Dice's coefficient on trigram profiles as metric for language similarity. 2013 International Conference Oriental COCOSDA held jointly with 2013 Conference on Asian Spoken Language Research and Evaluation (O-COCOSDA/CASLRE),
Office of the Registrar General & Census Commissioner, I. Office of the Registrar General & Census Commissioner, India. Office of the Registrar General & Census Commissioner, India. Retrieved 10/04/2019 from https://censusindia.gov.in/census.website/
Paulsen, J., Bergh, K., Chew, A., Gugerty, M. K., & Anderson, C. L. (2019). Wheat value chain: Bihar. Gates Open Res, 3(593), 593.
Podobnik, B., Grosse, I., Horvatić, D., Ilic, S., Ivanov, P. C., & Stanley, H. E. (2009). Quantifying cross-correlations using local and global detrending approaches. The European Physical Journal B, 71, 243-250.
Podobnik, B., Horvatic, D., Ng, A. L., Stanley, H. E., & Ivanov, P. C. (2008). Modeling long-range cross-correlations in two-component ARFIMA and FIARCH processes. Physica A: Statistical Mechanics and its Applications, 387(15), 3954-3959.
Podobnik, B., Horvatic, D., Petersen, A. M., & Stanley, H. E. (2009). Cross-correlations between volume change and price change. Proceedings of the National Academy of Sciences, 106(52), 22079-22084.
Podobnik, B., Jiang, Z.-Q., Zhou, W.-X., & Stanley, H. E. (2011). Statistical tests for power-law cross-correlated processes. Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 84(6), 066118.
Podobnik, B., & Stanley, H. E. (2008). Detrended Cross-Correlation Analysis: A New Method<? format?> for Analyzing Two Nonstationary Time Series. Physical review letters, 100(8), 084102.
Reboredo, J. C., Rivera-Castro, M. A., & Zebende, G. F. (2014). Oil and US dollar exchange rate dependence: A detrended cross-correlation approach. Energy economics, 42, 132-139.
Sanyal, S., Banerjee, A., Patranabis, A., Banerjee, K., Sengupta, R., & Ghosh, D. (2016). A study on improvisation in a musical performance using multifractal detrended cross correlation analysis. Physica A: Statistical Mechanics and its Applications, 462, 67-83.
Sardesai, M. (2019). Mother tongue blues. Retrieved 5/4/2019 from M. Sardesai
Sengupta, D., & Saha, G. (2015). Study on similarity among Indian languages using language verification framework. Advances in Artificial Intelligence, 2015(1), 325703.
Shimizu, Y., Thurner, S., & Ehrenberger, K. (2002). Multifractal spectra as a measure of complexity in human posture. Fractals, 10(01), 103-116.
Singh, C. M. (1996). A history of Manipuri literature. Sahitya Akademi.
Strazny, P. (2013). Encyclopedia of linguistics. Routledge.
Titze, I. R. (1995). Workshop on acoustic voice analysis: Summary statement. National Center for Voice and Speech.
Wang, F., Liao, G.-p., Zhou, X.-y., & Shi, W. (2013). Multifractal detrended cross-correlation analysis for power markets. Nonlinear Dynamics, 72, 353-363.
Witzel, M. (1999). Substrate languages in old indo-Aryan.(Ṛgvedic, middle and late vedic). Electronic Journal of Vedic Studies, 5(1), 1-67.
Xu, N., Shang, P., & Kamae, S. (2010). Modeling traffic flow correlation using DFA and DCCA. Nonlinear Dynamics, 61, 207-216.
Zhou, W.-X. (2008). Multifractal detrended cross-correlation analysis for two nonstationary signals. Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 77(6), 066211.
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