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WALS Online Resources for Sindhi
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: Max Planck Institute for Evolutionary Anthropology, 2021
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Glottolog 4.4 Resources for Sindhi Bhil
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: Max Planck Institute for Evolutionary Anthropology, 2021
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Glottolog 4.4 Resources for Sindhi
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: Max Planck Institute for Evolutionary Anthropology, 2021
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PHOIBLE 2.0 phonemic inventories for Sindhi
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: Max Planck Institute for the Science of Human History, 2019
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Handwritten Sindhi Character Recognition Using Neural Networks
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In: ISSN: 0254-7821 ; Mehran University Research Journal of Engineering and Technology ; https://hal.archives-ouvertes.fr/hal-01676725 ; Mehran University Research Journal of Engineering and Technology, Mehran University of Engineering and Technology, Jamshoro, Pakistan, 2018, 37 (1), pp.191-196 ; http://publications.muet.edu.pk/index.php/muetrj/article/view/122/63 (2018)
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Sindhi Bhil: a language of Pakistan
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: SIL International, 2018
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The influence of auditory-visual speech and clear speech on cross-language perceptual assimilation
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The influence of modality and speaking style on the assimilation type and categorization consistency of non-native speech
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Researching Sindhi and Urdu students’ reading habits and reading performance in a Pakistani university context
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Reading attitudes in L1 and L2 among rural and urban learners in a Pakistani context
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English medium for the government primary schools of Sindh, Pakistan ; an exploration of government primary school teachers’ attitudes
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Methods and Tools for Weak Problems of Translation ; Méthodes et outils pour les problèmes faibles de traduction
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In: https://tel.archives-ouvertes.fr/tel-00502192 ; Computer Science [cs]. Université Joseph-Fourier - Grenoble I, 2010. English (2010)
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A Finite State Model for Urdu Nastalique Optical Character Recognition
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In: http://paper.ijcsns.org/07_book/200909/20090915.pdf (2009)
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Abstract:
Finite state technology is being used since long to model NLP (Natural Language Processing) applications specially it has very successfully applied to machine translation and speech recognition systems. Character recognition in cursive scripts or handwritten Latin script also have attracted researchers ’ attention and some research is also done in this area. Optical character recognition is the translation of optically scanned bitmaps of printed or written text into digitally editable data files. OCRs developed for many world languages are already under efficient use but none exist for Nastalique – a calligraphic adaptation of the Arabic script, just as Jawi is for Malay. Urdu has 39 characters against the Arabic 28. Each character then has 2-4 different shapes according to their position in the word: initial, medial, final and isolated. In Nastalique, word and character overlapping makes optical recognition more complex. Optical character recognition of the Latin script is relatively easier. This paper based on research on Nastalique OCR discusses a proposed finite state model for the optical recognition of Nastalique printed text. Key words:
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Keyword:
Kurdish; Sindhi; Urdu; Uygur and Malay
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.554.1419 http://paper.ijcsns.org/07_book/200909/20090915.pdf
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