APPENDIX C. Phonetic Transcription Systems Widely Used in California Indian Language Materials

2019 ◽  
pp. 283-286
2012 ◽  
Vol 3 (2) ◽  
pp. 343-346
Author(s):  
Adabala Venkata Srinivasa Rao ◽  
D R Sandeep ◽  
V B Sandeep ◽  
S Dhanam Jaya

Recognition of Indian language scripts is a challenging problem. Work for the development of complete OCR systems for Indian language scripts is still in infancy. Complete OCR systems have recently been developed for Devanagri and Bangla scripts. Research in the field of recognition of Telugu script faces major problems mainly related to the touching and overlapping of characters. Segmentation of touching Telugu characters is a difficult task for recognizing individual characters. In this paper, the proposed algorithm is for the segmentation of  touching Hand written Telugu characters. The proposed method using Drop-fall algorithm is based on the moving of a marble on either side of the touching characters for selection of the point from where the cutting of the fused components should take place. This method improvers the segmentation accuracy higher than the existing one.


Author(s):  
Barbra A. Meek

This chapter is an exploration of how race and language become entangled in representations and ideas about what it means to be seen and recognized as Native American. Most conceptions of Indianness derive from scholarly European-derived representations and evaluations and from popular narrative media, the one often bootstrapping the other. In tandem, these public manifestations perpetuate the racialization of Indian languages and of Indianness, most ubiquitously in and through a discourse of “blood.” Several ideologies configure the racial logic that determines Indianness: purism (percentage of “Indian blood”), visibility (racialized—and cultural—manifestations of “blood”), continuity (maintenance of a pre-contact “bloodline”), and primitivism (expression of indigenous “blood” in and through language). I argue that this “ideological assemblage” (Kroskrity 2018) undergirds the processes of “racing Indian language(s)” and “languaging an Indian race” (H. Samy Alim 2016) that has resulted in propagating conflicts over and denials of Native American heritage.


Phonetica ◽  
1963 ◽  
Vol 10 (1-2) ◽  
pp. 42-50
Author(s):  
L.S. Harms

2015 ◽  
Vol 112 (41) ◽  
pp. 12752-12757 ◽  
Author(s):  
Gerhard Jäger

Computational phylogenetics is in the process of revolutionizing historical linguistics. Recent applications have shed new light on controversial issues, such as the location and time depth of language families and the dynamics of their spread. So far, these approaches have been limited to single-language families because they rely on a large body of expert cognacy judgments or grammatical classifications, which is currently unavailable for most language families. The present study pursues a different approach. Starting from raw phonetic transcription of core vocabulary items from very diverse languages, it applies weighted string alignment to track both phonetic and lexical change. Applied to a collection of ∼1,000 Eurasian languages and dialects, this method, combined with phylogenetic inference, leads to a classification in excellent agreement with established findings of historical linguistics. Furthermore, it provides strong statistical support for several putative macrofamilies contested in current historical linguistics. In particular, there is a solid signal for the Nostratic/Eurasiatic macrofamily.


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