A Survey: Accretion in Linguistic Classification of Indian Languages

2021 ◽  
pp. 133-145
Author(s):  
Dipjayaben Patel
2000 ◽  
Vol 29 (1) ◽  
pp. 150-153 ◽  
Author(s):  
Victor Golla

For more than a decade, Americanists have been working in the shadow of Greenberg's Language in the Americas (1987) and the hemisphere-wide classification of American Indian languages proposed there. Greenberg's work, based for the most part on naïve comparisons of lexical data with which he was largely unfamiliar, was met with considerable skepticism by scholars familiar with the problems of American linguistic classification. But Greenberg, a senior linguist who is widely recognized as the father of modern linguistic typology, aggressively defended his methods and results, and he made allies among geneticists and archeologists who found that his tripartite classification (Eskimo-Aleut, Na-Dene, and “Amerind”) dovetailed with some of their own ideas. Moreover, his book was published by a leading university press. Mainly for these reasons – certainly not for its critical acceptance – Language in the Americas has become a standard reference work. It is in most academic libraries in North America, and in many it is given a place of honor on the reference shelf – together with Merritt Ruhlen's Guide to the world's languages, I: Classification (published by the same press, 1987), which, at least for the Americas, does little more than uncritically recapitulate Greenberg.


Author(s):  
Muxtasar Muminova

Таржима илми ва амалиётида ўгириш қийин бўлган сўзлар бир талай. Уларнинг асосийлари миллий ўзига хос сўзлар бўлиб, халқаро терминда реалиялар дейилади. Бу муаммоларнинг ечими, уларнинг таснифи ва тавсифи таржима назариясида ўрганилмоқда. Умумий қонун-қоидалар билан бирга ҳар бир тил жуфтлигида махсус қоидалар ишлаб чиқилмоғи лозим. Чет тиллардан ўзбек тилига ўгирилаётган асарларда ана шу муаммолар ҳанузгача таржимонлар ва муҳаррирларнинг бошини қотириб келмоқда. Ушбу мақолада асосан бошқа тиллардаги атоқли отлар тоифасига кирувчи киши номлари таржимаси ва ўзбек тилида ёзилиши ҳақида фикр юритамиз.  


2020 ◽  
Vol 17 (2) ◽  
pp. 127-144
Author(s):  
Michael Erdman

AbstractThe current work is an exploration of the life and linguistic scholarship of the Crimean Tatar linguist Bekir Çobanzade. In it, I pay particular attention to the impact of the author's socio-political environment, especially the rise of Stalinism, on his works relating to the history and classification of the Turkic languages. I demonstrate how these circumstances compelled Çobanzade to perform an intellectual migration, from an indigenous Turkic ontology focused on the structural wholeness of the Turkic languages to a rigid application of Marxist-Leninist concepts of socially-determined linguistic classification. I do this with the help of monographs and journal articles published in Crimean Tatar, Ottoman Turkish, Azerbaijani and Russian, problematizing the multitude of his audiences and loyalties. As such, Çobanzade's story becomes a microcosm of the experience of a broader generation of Turkic writers and scholars. It was a generation that sought to take the greatest benefit from the monumental changes following World War I, and ended up being consumed by the totalitarian state that emerged in its wake. Çobanzade is one victim of many whose scholarly oeuvre can open a window to a heady and bygone period of experimentation and change.


Author(s):  
R. SANJEEV KUNTE ◽  
R. D. SUDHAKER SAMUEL

Optical Character Recognition (OCR) systems have been effectively developed for the recognition of printed characters of non-Indian languages. Efforts are underway for the development of efficient OCR systems for Indian languages, especially for Kannada, a popular South Indian language. We present in this paper an OCR system developed for the recognition of basic characters in printed Kannada text, which can handle different font sizes and font sets. Wavelets that have been progressively used in pattern recognition and on-line character recognition systems are used in our system to extract the features of printed Kannada characters. Neural classifiers have been effectively used for the classification of characters based on wavelet features. The system methodology can be extended for the recognition of other south Indian languages, especially for Telugu.


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