This work is first attempt towards English to Urdu Machine Translation (MT) using example based approach. We have developed an interactive MT system to facilitate the user to customize the translation to his needs, thereby improving the performance of the translation. Our MT system supports idioms, homographs, and some other features in addition to the ability of the bilingual corpus to evolve....

This paper presents an optical character recognition system for the handwritten Urdu Digits. A lot of work has been done in recognition of characters and numerals of various languages like Devanagari, English, Chinese, and Arabic etc. But in case of handwritten Urdu Digits very less work has been reported. Different Daubechies Wavelet transforms are used in this work for feature extraction. Als...

Text Segmentation is one of the critical and vital step in OCR system of any language because accuracy of OCR depends upon correctly segmented characters. Segmentation divide the text images into its constituent parts (i.e. lines, components or words and individual characters). As Urdu and Arabic are highly cursive and context sensitive in nature and have improper space between words therefore,...

We present a hybrid NER (Name Entity Recognition) system for Urdu script by integration of n-gram model (unigram and bigram), rules and gazetteers. We used prefix and suffix characters for rule construction instead of first name and last name lists or potential terms on the output list that is produced by n-gram model. Evaluation of the system is performed on two corpora, the IJCNLP NE (Named E...

Both Inflectional and derivational morphology lead to multiple surface forms of a word. Stemming reduces these forms back to its stem or root, and is a very useful tool for many applications. There has not been any work reported on Urdu stemming. The current work develops an Urdu stemmer or Assas-Band and improves the performance using more precise affix based exception lists, instead of the co...

Preprocessing is a preliminary step in many fields including IR and NLP. The effect of basic preprocessing settings on English for text summarization is well-studied. However, there is no such effort found for the Urdu language (with the best of our knowledge). In this study, we analyze the effect of basic preprocessing settings for single-document text summarization for Urdu, on a benchmark co...

In this work, Portuguese, Polish, English, Urdu, and Arabic automatic speech recognition evaluation systems developed by the RWTH Aachen University are presented. Our LVCSR systems focus on various domains like broadcast news, spontaneous speech, and podcasts. All these systems but Urdu are used for Euronews and Skynews evaluations as part of the EUBridge project. Our previously developed LVCSR...

Determining and modeling phonological phenomena is necessary to generate speech from textual input. These phenomena include letter to sound conversion, syllabification, sound change, stress assignment and intonation assignment. This paper presents work on Urdu phonological processes and provides algorithms to convert textual input into phonologically annotated output, required for Urdu text-to-...

This paper introduces a two-way Urdu– Roman transliterator based solely on a nonprobabilistic finite state transducer that solves the encountered scriptural issues via a particular architectural design in combination with a set of restrictions. In order to deal with the enormous amount of overgenerations caused by inherent properties of the Urdu script, the transliterator depends on a set of ph...