نتایج جستجو برای: phnilogical error urdu language
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Machine Translation, (hereafter in this document referred to as the "MT") faces a lot of complex problems from its origination. Extracting multiword expressions is also one of the complex problems in MT. Finding multiword expressions during translating a sentence from English into Urdu, through existing solutions, takes a lot of time and occupies system resources. We have designed a simple rela...
SYSTRAN started the design and the development of Arabic, Farsi and Urdu to English machine translation systems in July 2002. This paper describes the methodology and implementation adopted for dictionary building and morphological analysis. SYSTRAN’s IntuitiveCoding® technology (ICT) facilitates the creation, update, and maintenance of Arabic, Farsi and Urdu lexical entries, is more modular an...
Automatic Speech Recognition (ASR) is a key component in Human Computer Interaction (HCI) applications. Stability of ASR systems largely depends on accent, gender, age of speakers, background noise and channel variations. In this paper, a study has been conducted to classify five different accents of Urdu language spoken in Pakistan i.e. Punjabi, Urdu, Pashto, Saraiki and Sindhi. Speech data ha...
Named Entity Recognition (NER) is a task which helps in finding out Persons name, Location names, Brand names, Abbreviations, Date, Time etc and classifies them into predefined different categories. NER plays a major role in various Natural Language Processing (NLP) fields like Information Extraction, Machine Translations and Question Answering. This paper describes the problems of NER in the c...
Urdu is spoken by more than 100 million speakers. This paper summarizes the corpus and lexical resources being developed for Urdu by the CRULP, in Pakistan.
Metalinguistic awareness is the ability to attend to, and reflect upon, the properties of a language. Metalinguistic awareness is often assessed using tasks of phonological and syntactical awareness (see, e.g., Bialystok & Herman, 1999; Bowey, 1990; McGuiness, 2005, for reviews). Tests of phonological awareness usually require the analysis of sounds in words, whereas tests of syntactical awaren...
BACKGROUND Numerous study tools on diabetes self-care have been introduced; however, most existing tools do not show expectable and meaningful correlations with patients' glycaemic control. The Diabetes Self-Management Questionnaire (DSMQ) was designed to appraise self-care activities which can predict glycaemic control outcomes. However, this tool has not been validated in Pakistan. Therefore,...
Building robust text recognition systems for languages with cursive scripts like Urdu has always been challenging. Intricacies of the script and the absence of ample annotated data further act as adversaries to this task. We demonstrate the effectiveness of an end-to-end trainable hybrid CNN-RNN architecture in recognizing Urdu text from printed documents, typically known as Urdu OCR. The solut...
In this paper we explore the possibility of using cross lingual projections that help to automatically induce role-semantic annotations in the PropBank paradigm for Urdu, a resource poor language. This technique provides annotation projections based on word alignments. It is relatively inexpensive and has the potential to reduce human effort involved in creating semantic role resources. The pro...
Text reuse is the act of borrowing text from existing documents to create new texts. Freely available and easily accessible large online repositories are not only making reuse of text more common in society but also harder to detect. A major hindrance in the development and evaluation of existing/new mono-lingual text reuse detection methods, especially for South Asian languages, is the unavail...
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