In this study, we present a brief overview of Named Entity Recognition (NER) system, various approaches followed for NER systems and finally NER systems for Urdu language. Urdu language raises several challenges to Natural Language Processing (NLP) largely due to its rich morphology. Research against NER systems in Urdu language is at infancy stage therefore the focus of this study is on challe...

The recognition of cursive script is regarded as a subtle task in optical character recognition due to its varied representation. Every cursive script has different nature and associated challenges. As Urdu is one of cursive language that is derived from Arabic script, that’s why it nearly shares the same challenges and difficulties even more harder. We can categorized Urdu and Arabic language ...

This work presents the development and evaluation of an extended Urdu parser. It further focuses on issues related to this parser and describes the changes made in the Earley algorithm to get accurate and relevant results from the Urdu parser. The parser makes use of a morphologically rich context free grammar extracted from a linguistically-rich Urdu treebank. This grammar with sufficient enco...

A new large Urdu handwriting database, which includes isolated digits, numeral strings with/without decimal points, five special symbols, 44 isolated characters, 57 Urdu words (mostly financial related), and Urdu dates in different patterns, was designed at Centre for Pattern Recognition and Machine Intelligence (CENPARMI). It is the first database for Urdu off-line handwriting recognition. It ...

This study examined differences in residence, marriage age, and education among 6 language groups (Balochi-Brohi, Urdu, Siraiki, Punjabi, Sindhi, and Pushto) in Pakistan. Ethnic differences were reported for fertility preferences and family planning attitudes, knowledge, and practices. Data were obtained from the 1990-91 Pakistan Demographic and Health Survey among 6582 eligible ever-married ...

The paper presents a design schema and details of a new Urdu POS tagset. This tagset is designed due to challenges encountered in working with existing tagsets for Urdu. It uses tags that judiciously incorporate information about special morpho-syntactic categories found in Urdu. With respect to the overall naming schema and the basic divisions, the tagset draws on the Penn Treebank and a Commo...

Urdu language raises several challenges to Natural Language Processing (NLP) largely due to its rich morphology. In this language, morphological processing becomes particularly important for Information Retrieval (IR). The core tool of IR is a Stemmer which reduces a word to its stem form. Due to the diverse nature of Urdu, developing stemmer is a challenging task. In Urdu, there are large numb...

-Natural Language Processing is the multidisciplinary area of Artificial Intelligence, Machine Learning and Computational Linguistic for processing human language automatically. It involves understanding and processing of human language. The way through which we share our contents or feelings have always great importance in understanding and processing of language. Parsing is the most suited ap...

This paper presents an online system for recognizing isolated, hand-sketched Urdu characters drawn on a Tablet PC. Attributes of Urdu characters are analyzed to define a set of features which are then trained and classified using a weighted, linear classifier. As a proof of concept, we have integrated our recognition algorithm into an application used to help people learn the Urdu language. Pre...

This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. Research h...