In the search of new approaches to the problem of emergence and evolution of natural languages, Mathematics, Theoretical Computer Science, as well as Molecular Biology and Neuroscience, both deeply penetrated and profoundly inspired by concepts originated in Mathematics and Computer Science, represent today the richest pools of formal concepts, structures, and methods to borrow and to adapt

Belaga, Edward G.

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Emergence and Evolution of Natural Languages:New Mathematical & Algorithmic PerspectivesEdward G. BelagaFebruary 15, 2011In their recent influential paper Language Evolution : The Hardest ProblemIn Science ? [1], Morten H. Christiansen et Simon Kirby wrote: “Language isone of the hallmarks of the human species – an important part of what makes ushuman. Yet, despite a staggering growth in our scientific knowledge about theorigin of life, the universe and (almost) everything else that we have seen fit toponder, we know comparatively little about how our unique ability for languageoriginated and evolved into the complex linguistic systems we use today. Whymight this be ? ”In the search of new approaches to the problem of emergence and evolutionof natural languages, Mathematics, Theoretical Computer Science, as well asMolecular Biology and Neuroscience, both deeply penetrated and profoundlyinspired by concepts originated in Mathematics and Computer Science, rep-resent today the richest pools of formal concepts, structures, and methods toborrow and to adapt.The mathematical and computational methods, both well-known [2] andnew ones [3], have both the potential and good prospectives to be used in theautomatic treatment of natural languages [4], viewed as formal structures, andin the formal simulation of their emergence and evolution, free from linguisticintricacies of the historical prospective.On the other hand, it has been shown that such a perspective could be takeninto account with the help of mathematical and computational methods commonfor modern biological evolutionary studies. In particular, these methods havepermitted recently to shed a new light [5] into the origins of the Indo-Europeanlanguage family, “the most intensively studied, yet still most recalcitrant, problemof historical linguistics” [6]. As to the Neuroscience end of this vast researchenterprise, one looks here for “the action origins of language, via the MirrorNeuron System” [7].The approach which we are advancing in the present study is building onsome implications of the well-known but almost universally disregarded semanti-cally meaningful tight combinatorial and topological morphological structure ofthe verbal system of Semitic languages, and in particular, of Biblical Hebrew [8],to show that the corresponding linguistic fossils testify to the existence of a nowextinct Proto-Language whose extremely tight verbal organization and mean-1ingful architecture made it both structurally strikingly similar and expressivelyvastly superior to humanly designed Assembler languages [9], – an absolutelynovel, paradoxical phenomenon, never before and nowhere else observed andcrying out for new explanatory linguistic paradigms.Besides its intrinsic value, our approach has the obvious potential to bothvalidate “action to language” Neuroscience conjectures, by suggesting theirnovel and authentic interpretation, and to provide a new and, for that matter,extremely rich testing ground for the aforementioned mathematical and com-putational methods of simulation and analysis of natural languages.References[1] M. Christiansen, S. Kirby, Language Evolution : The Hardest Problem InScience ? In: Language Evolution, eds. M. Christiansen, S. Kirby, OxfordUniversity Press, pp. 1-15 (2003).[2] A. Biermann, B. Ballard [1980] : Toward Natural Language Computation.American Journal of Computational Linguistics 6, 71-86 (1980).[3] L. Zadeh, Precisiated Natural Language –Toward a Radical Enlargementof the Role of Natural Languages in Information Processing, Decision andControl. In: Proceedings of the 9th International Conference on NeuralInformation Processing (ICONIP’OZ) , Vol. 1, eds. Lipo Wang, Jagath C.Rajapakse, Kunihiko Fukushima, Soo-Young Lee, and Xin Yao (2002).[4] A. Mehler, R. Köhler, Introduction: Machine Learning in a Semiotic Per-spective. In: Aspects of Automatic Text Analysis, eds. A. Mehler, R. Köh-ler, Series: Studies in Fuzziness and Soft Computing 209, Springer (2007).[5] R. Gray, Q. Atkinson, Language-tree divergence times support the Anato-lian theory of Indo-European origin. Nature 426, 435-439 (2003).[6] J. Diamond, P. Bellwood, Farmers and their languages: the first expan-sions. Science 300, 597Ð603 (2003).[7] M. Arbib, ed., Action to Language via the Mirror Neuron System. Cam-bridge University Press (2006).[8] L. McFall,The Enigma of the Hebrew Verbal System: Solutions from Ewaldto the Present Day, The Almond Press, Cambridge (1982).[9] M. Johnson. Assembly Language: For Real Programmers Only! PrenticeHall Computer Pub, Upper Saddle River, NJ (1993).Edward G. BELAGAInstitut de Recherche Mathématique Avancée de Strasbourg7 rue René Descartes, F-67084 Strasbourg Cedex, FRANCEe-mail: edward.belaga@math.u-strasbg.fr2

Emergence and Evolution of Natural Languages: New Mathematical & Algorithmic Perspectives

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Emergence and Evolution of Natural Languages: New Mathematical & Algorithmic Perspectives

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