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Journal articles on the topic 'Urdu language'
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1
Dr. Aasma Rani, Dr. Aqsa Naseem Sindhu, and Dr. Sadaf Naqvi. "MUTUAL TRANSLATIONS OF URDU AND PUNJABI." Tasdiqتصدیق۔ 4, no. 01 (June 30, 2022): 54–63. http://dx.doi.org/10.56276/tasdiq.v4i01.91.
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Human being uses language to convey their messages, emotions, feelings, observations and experiences to others. For this, language was used as spoken and written language, and different languages came into existence due to geographical boundaries and linguistic groups. And for those who know one language, commonly it is not possible to know another language. Human emotions and feelings are expressed in one language in speech or writing which the other language knower is generally unable to understand. Thus there was a need to translate this expression into another language which was called Translation. This Tradition of translation is also found in the Urdu language, Urdu is also influenced by international and regional languages and it has also had its effects on these languages that are why there is a wide and coherent series of translations of international literature into Urdu and Urdu literature into foreign languages. On the other hand, there is a strong tradition of Urdu translations of regional languages such as Sindhi, Seraiki, Pashto, Balouchi, Brahui and Punjabi literature, and a well-built tradition of translation from Urdu literature into these regional languages. In this article, we will discuss the tradition and importance of Urdu to Punjabi and Punjabi to Urdu translations.
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Dr. Tahmina Abbas. "The revival of Urdu language and Sir Syed Ahmad Khan." Noor e Tahqeeq 6, no. 04 (November 13, 2022): 41–46. http://dx.doi.org/10.54692/nooretahqeeq.2022.06041830.
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Sir Syed Ahmad Khan had verstyle personality. At the time when Sir Syed's literary period began, there was no notable prose creation in the Urdu language except the story. During this period, Urdu was the spoken language, but Persian was given priority for writing and compilation. Sir Syed's far-sighted eyes examined all these reasons and found ways for the development of Urdu language. With his efforts, Sir Syed made Urdu one of the top languages of the world. He wrote articles in Urdu with fluency and with his influence. His articles published in "Tehbihul-ul-Akhlaq" have priority among Urdu articles. His works written in Urdu language, ‘‘Tarikh Sarkshi Bijnoor’’, ‘‘Risala Asaab Baghawat e Hind’’, “Khutbat-e- Ahmadiyya”, “Aasaar e sanadeed”, are counted among the important works of this period. Sir Syed is the founder of modern Urdu prose. The language has been given an important place among the important languages of the world. In this paper, the efforts made by Sir Syed Ahmed Khan regarding the revival of Urdu language and literature have been studied.
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DATLA, KAVITA. "A Worldly Vernacular: Urdu at Osmania University." Modern Asian Studies 43, no. 5 (September 2009): 1117–48. http://dx.doi.org/10.1017/s0026749x08003715.
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AbstractTwinned as Urdu has become with the fate of India's largest religious minority, Muslims, and with the emergence of the independent state of Pakistan, for which Urdu is the official national language, the story of Urdu holds a peculiar place and a special significance in histories of the subcontinent. Stories of the Urdu language are dramatic, bound up as they are in questions of politics, the fate of Hindus and Muslims and the vicissitudes of both the Urdu and the Hindi languages. Though Hindi–Urdu language politics are an important part of these languages' colonial history, this article emphasizes another story. For, like the other vernaculars of south Asia, Urdu had to contend as much with English as with Hindi, and it is that story that is emphasized here. This article details how early-twentieth-century Hyderabad's Urdu educators engaged with questions of native education, language, and Western science. It highlights the discussions and disagreements that accompanied this educational project as Urdu advocates re-evaluated their language and its sources of authority, attempting to make the Urdu language a worldly vernacular, useful for more than the subcontinent's Muslim population.
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Alam, Mehreen, and Sibt Ul Hussain. "Roman-Urdu-Parl: Roman-Urdu and Urdu Parallel Corpus for Urdu Language Understanding." ACM Transactions on Asian and Low-Resource Language Information Processing 21, no. 1 (January 31, 2022): 1–20. http://dx.doi.org/10.1145/3464424.
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Availability of corpora is a basic requirement for conducting research in a particular language. Unfortunately, for a morphologically rich language like Urdu, despite being used by over a 100 million people around the globe, the dearth of corpora is a major reason for the lack of attention and advancement in research. To this end, we present the first-ever large-scale publicly available Roman-Urdu parallel corpus, Roman-Urdu-Parl, with 6.37 million sentence-pairs. It is a huge corpus collected from diverse sources, annotated using crowd-sourcing techniques, and also assured for quality. It has a total of 92.76 million Roman-Urdu words, 92.85 million Urdu words, Roman-Urdu vocabulary of 42.9 K words, and Urdu vocabulary of 43.8 K words. Roman-Urdu-Parl has been built to ensure that it not only captures the morphological and linguistic features of the language but also the heterogeneity and variations arising due to demographic conditions. We validate the authenticity and quality of our corpus by using it to address two natural language processing research problems, that is, on learning word embeddings and building a machine transliteration system. Our contribution of the corpus leads to exceptional results in both settings, for example, our machine transliteration system sets a new state-of-the-art with a Bilingual Evaluation Understudy (BLEU) score of 84.67. We believe that Roman-Urdu-Parl can serve as fuel for igniting and advancing works in many research areas related to the Urdu language.
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Ali Raza Siddique, Muhammad Ahmad, and Dr. Muhammad Asim Mahmood. "Identification of Boosters as Metadiscourse across Punjabi and Urdu Languages: A Machine Translation Approach." Research Journal of Social Sciences and Economics Review (RJSSER) 2, no. 1 (March 7, 2021): 208–22. http://dx.doi.org/10.36902/rjsser-vol2-iss1-2021(208-222).
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Boosters are said to function appropriately as metadiscourse features across languages. This study, therefore, aimed to investigate the functions and appropriateness of the metadiscourse features across Punjabi and Urdu languages. For this purpose, a list of 79 boosters (as metadiscourse features) was considered that (boosters) were first transliterated across Punjabi and Urdu languages employing a machine translation process. Punjabi translation was carried through ‘Akhar’ (a software), and Punjabi corpus (a tool). Whereas Urdu translation was realized through online Urdu thesaurus, and ‘ijunoon’ (an online dictionary). Machine transliteration was followed by manual cleansing of Punjabi and Urdu translated wordlists that helped identify boosters in the corpora. Appropriateness of the identified boosters was then realized through expert opinion and Punjabi corpus (for the Punjabi language), and expert opinion, online Urdu thesaurus, and Urdu WordNet (for the Urdu language). This process further guided about how to; make wordlists, filter as well as verify translated words, and offer interactional and interactive metadiscourse categories across Punjabi and Urdu languages.
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Ayesha Saddiqa. "The Role of Pashto (as L1) and Urdu (as L2) in English Language Learning." Linguistics and Literature Review 4, no. 1 (March 30, 2018): 1–17. http://dx.doi.org/10.32350/llr.v4i1.273.
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Pashto is one of the dominant languages in the north of Pakistan. Its speakers prefer to communicate in L1with their peers in non-pashto speaking regions like Lahore, which is the capital city of Punjab, Pakistan. Along with Pashto, they communicate in Urdu (the national language) and English (the most prestigious academic language) for higher education, employment and business. With this background in mind, the current study investigates: (a) what are the common syntactic properties (sentence structure, aspect, preposition, article and mood) in Pashto, Urdu and English languages?, (b) What are the advantages and/ or disadvantages to Pashto speakers in English language learning? and (c) What is the potential role of Urdu in English language learning? Linguistic Proximity Model was used as a theoretical framework to analyze the data. The data was gathered from 19 Bachelor of Science Pashto students of different programs from three universities located in Lahore. The participants were asked to translate sentences from Urdu to English and from Pashto to English to find interference of both Pashto and Urdu in learning the English language. Unlike many studies, the present study negates the facilitative role of background languages in learning the target language. Apparently, although Urdu serves as a base for learning the English language, the present study recommends an independent investigation to explore the role of the Urdu language in learning English.
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JAFAR, MUHAMMAD RAHIM, and MUHAMMAD RAHIM JAFAR. "Challenges toward the Implications of Official Urdu." Pacific International Journal 5, no. 4 (December 31, 2022): 33–37. http://dx.doi.org/10.55014/pij.v5i4.234.
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Urdu is associated with the Muslims of the subcontinent region before the partition of Pakistan and India. It is the national language and one of the official languages of Pakistan. English and Urdu are spoken, written, and understood throughout the country, although the Urdu languages are spoken throughout many regions of Pakistan, including the local and regional languages. For the same reason, Urdu was declared Pakistan's national language after the country gained independence.Afterwards, certain bodies were established for its proper implementation as the official language of the country. Implementation of this constitutional obligation, though, requires a thorough exercise and hard work for the development of languages in Pakistan, such as the competing status of Urdu and English Therefore, academia, constitutionalists, and the general public are suggested to come forward to help the government official fulfil this obligation.
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Muhammad, Khalid Bin, and S. M. Aqil Burney. "Innovations in Urdu Sentiment Analysis Using Machine and Deep Learning Techniques for Two-Class Classification of Symmetric Datasets." Symmetry 15, no. 5 (May 5, 2023): 1027. http://dx.doi.org/10.3390/sym15051027.
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Many investigations have performed sentiment analysis to gauge public opinions in various languages, including English, French, Chinese, and others. The most spoken language in South Asia is Urdu. However, less work has been carried out on Urdu, as Roman Urdu is also used in social media (Urdu written in English alphabets); therefore, it is easy to use it in English language processing software. Lots of data in Urdu, as well as in Roman Urdu, are posted on social media sites such as Instagram, Twitter, Facebook, etc. This research focused on the collection of pure Urdu Language data and the preprocessing of the data, applying feature extraction, and innovative methods to perform sentiment analysis. After reviewing previous efforts, machine learning and deep learning algorithms were applied to the data. The obtained results were compared, and hybrid methods were also recommended in this research, enabling new avenues to conduct Urdu language data sentiment analysis.
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Murtaza, Hafiz Ghulam, and Dr Almas Khanum. "Background of Urdu Script." Noor e Tahqeeq 7, no. 03 (September 27, 2023): 45–55. http://dx.doi.org/10.54692/nooretahqeeq.2023.07032024.
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The story of the origin of script is hidden in the deep veils of the past and to reach it, the origin of language has to be considered. It is certain that the language was born before the script and reached the destination of meaningful words after completing a cultural journey of many centuries. Script refers to the written expression of a language through specific words. Every script has its own limitations as per its use and applicability. All languages have specific scripts with certain qualities and shortcomings. Oriental languages also use different scripts with many variations such as ‘Naskh’, ‘Kufi’ and ‘Nastaliq’. Origin and development of these scripts in relation to the Urdu language and its script have been analyzed in this article with special historic perspective.
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Faiza Mushtaq, Sumaira Hashmi, and Fasiha Maryam. "OBSOLETE WORDS IN URDU LANGUAGE." Inception - Journal of Languages and Literature 2, no. 1 (June 24, 2022): 1–19. http://dx.doi.org/10.36755/ijll.v2i1.7.
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Urdu is the national language of Pakistan. It is a standardized register of Hindustani language and is lingua franca of Pakistan. Urdu is the official language of six Indian states. The study aims to investigate how language is dying out within the language the words are obsoleted from Urdu language. The target population for this study was Native speaker of Urdu language of 11-25 years age, 26-40 years age, 41-55 and 60 years & above of age. The sample consisted of 20 people each group. The data was obtained through wordlist of 60 chosen words and then in the end, interviews were administered to decipher the language attrition in Urdu language. Triangulation approach was used for data analysis. The data of 65 respondents was analyzed using statistical tests in order to compare the performance of native and non-native speakers of Urdu language. Their motivation was also examined. Results revealed that in native speech community, the speakers of 41-55 age groups know many words along with its correct meanings and correct usage and the ratio was not that bad even in the group of participants who are aged 26-40. But in the group aged 11-25 the ratio is alarmingly low. The language is not transmitted to the next generation because the parents of this age group themselves did not acquire Urdu as their first language. Language is not documented in modern time that is why it is changing. There are many other words from other languages that are replacing the actual word of Urdu language. Speakers are using those words for convenience purpose as well. The need of the time is to document the language with its essence to prove its antiquity.
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Kurd, Shehla Anwer, and Saima Hassan. "ATTITUDE OF BALOCHISTAN’S YOUTH TOWARDS INDIGENOUS LANGUAGE BRAHUI AS COMPARED TO URDU AND ENGLISH: A CASE STUDY OF (SBK) SARDAR BAHADUR KHAN WOMEN UNIVERSITY, QUETTA." Pakistan Journal of Social Research 04, no. 01 (March 31, 2022): 785–92. http://dx.doi.org/10.52567/pjsr.v4i1.943.
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This research aims to compare the attitudes of Balochistan’s youth towards indigenous language i.e. Brahui in comparison to Urdu and English. It explores instrumental and integrative motivations of participants towards these languages. The study adopted quantitative paradigm, a questionnaire as a research instrument. The data was collected from 90 participants of Brahui speakers. The data was analyzed by the SPSS program through frequency and mean analysis. The study concludes that participants’ attitudes were positive towards English language, neutral to Urdu language and negative towards Brahui language. The participants showed highly positive (instrumental and integrative) motivation towards Brahui vs Urdu languages. This study also determines other dominant languages spoken in Balochistan that are Balochi and Pashto. Keywords: Language attitude, Indigenous language, instrumental motivation, integrative motivation.
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Kazmi, Sarah Syed. "THE HISTORY OF REPRESENTATION IN THE INDIAN SUBCONTINENT: THE GENESIS OF A NEW LINGUA FRANCA." Pakistan Journal of Social Research 04, no. 04 (December 31, 2022): 757–62. http://dx.doi.org/10.52567/pjsr.v4i04.889.
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The South Asian Subcontinent has experienced invasions from different directions. In the ancient period we see Sanskrit and Pali, Prakrit and proto -Hindi languages evolve. With the advent of the Muslim conquerors, Persian the cultural language of the Ajam, became the court and official language. There was a natural intermingling of both peoples with different language tradition and a local dialect first called Hindavi emerged. The word Urdu meant Cantonment in Turkish. Where exactly in South Asia Urdu began to be used and recognized has become a matter of scholarly contention, which is traced here. The British invasion and the subsequent foundation of Fort William in Calcutta in 1800 led to the dissemination of both Urdu and Hindi and the political interplay of languages. This article delves into the role of the colonial power in promoting a language or a set of languages. It further dilates as to how lending a religious veneer to a certain language by design can further bolster its power positioning, particularly if the language is common among the lower denomination of the economic strata. Urdu was variously known as Hindavi, Deccani and the later more exalted epithet; Urdu i Mualla. The Islamization of Urdu and the Sanskritization of Hindi unravel efforts aimed at bifurcating languages along socio-religious lines preponderantly by the colonial agency. Thus, the apparent patronage for indigenous languages on the part of the Orientalists turned out to be a colonial venture driven by the ulterior motive to prolong colonial foothold in the Indian Subcontinent and to mitigate chances of rebellion. The article deliberates upon the making of a new lingua franca in the then Subcontinent which was home to a host of multicultural and multiethnic communities. Keywords: Lingua Franca, Hindavi, Urdu i Mualla, Deccani, Fort William College, Multicultural, Multiethnic, Sanskritizarion, Islamization, Marginalization.
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Ansari, Zahra, Shaukat Ali, and Fatima Khan. "USE OF ROMAN SCRIPT FOR WRITING URDU LANGUAGE." International Journal of Linguistics and Culture 1, no. 2 (December 31, 2020): 165–78. http://dx.doi.org/10.52700/ijlc.v1i2.20.
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The purpose of the paper is to highlight the need of evolving a standardized Romanization table, which is used for writing Urdu language on mobile phones, laptops or tabs etc. Use of Urdu language in Roman script is in vogue in our daily life. Internet and mobile users have conveniently adopted Roman script since long for writing Urdu. But it is being used in an irregular and disorganized way. Therefore, an organized and systematic Roman script is imperative to explore ample possibilities of its usage. The current study is qualitative in nature. The Urdu Romanization table is used as a tool in this regard. This tool has been framed by finding out equivalents of Urdu alphabets in the Roman letters so that the sounds and etymology of the traditional Pearsio Arabic script of Urdu from different languages (Sanskrit, Persian, Arabic, and Turkish) could be used and preserved in a proper way.
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Octaviani, Anisa. "TAHLIL AL MUFRODATI AL 'ARABIYYATI AL DAKHILATI ILA AL LUGHATI AL URDIYYATI." Nazharat: Jurnal Kebudayaan 27, no. 1 (January 5, 2022): 71–90. http://dx.doi.org/10.30631/nazharat.v27i1.55.
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This study discusses the analysis of Arabic vocabulary into Urdu. Urdu is one of the languages in India and is the official language in Pakistan and Bangladesh. Urdu language with its development is heavily influenced by Arabic because during the Islamic era, its expansion was very rapid in the Indian Subcontinent.The purpose of this study is to: ) Knowing what Arabic vocabulary is used by Urdu in the Google Play Store application ) Knowing the changes in writing Arabic vocabulary into Urdu. ) Knowing the sound changes in Arabic vocabulary into Urdu. ) Knowing the changes in the meaning of Arabic vocabulary into Urdu. The type of research used is qualitative research. It can be concluded from the results of this study: ) There are Arabic vocabulary that goes into Urdu on the Google Play Store application ) There is a change in writing Arabic vocabulary that goes into Urdu ) There is a change in the sound of Arabic vocabulary that goes into Urdu. in urdu ) There is a change in the meaning of arabic vocabulary into urdu.
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Dr. Jan Nisar Moin. "A Research Review of Urdu Language." Dareecha-e-Tahqeeq 2, no. 3 (March 21, 2022): 1–70. http://dx.doi.org/10.58760/dareechaetahqeeq.v2i3.23.
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Urdu originated in the 12th century AD from the Upabharmsha region of northwestern India, which served as a linguistic system after the Muslim conquest. His first great poet was Amir Khosrow (1253–1325), who wrote duets, folk songs, and riddles in the newly formed speech, which was then called Hindu. This mixed speech was spoken in different ways in Hindi, Hindi, Hindi, Delhi, Rekhta, Gujari, Dakshini, Urdu, Mullah, Urdu, or Urdu only. The great Urdu writers continued to call it Hindi or Hindi until the beginning of the 19th century, although there is evidence that it was called Indian in the late 17th century. This article presents a research overview of Urdu language.
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Rafique, Ayesha, Kamran Malik, Zubair Nawaz, Faisal Bukhari, and Akhtar Hussain Jalbani. "Sentiment Analysis for Roman Urdu." Mehran University Research Journal of Engineering and Technology 38, no. 2 (April 1, 2019): 463–70. http://dx.doi.org/10.22581/muet1982.1902.20.
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The majority of online comments/opinions are written in text-free format. Sentiment Analysis can be used as a measure to express the polarity (positive/negative) of comments/opinions. These comments/ opinions can be in different languages i.e. English, Urdu, Roman Urdu, Hindi, Arabic etc. Mostly, people have worked on the sentiment analysis of the English language. Very limited research work has been done in Urdu or Roman Urdu languages. Whereas, Hindi/Urdu is the third largest language in the world. In this paper, we focus on the sentiment analysis of comments/opinions in Roman Urdu. There is no publicly available Roman Urdu public opinion dataset. We prepare a dataset by taking comments/opinions of people in Roman Urdu from different websites. Three supervised machine learning algorithms namely NB (Naive Bayes), LRSGD (Logistic Regression with Stochastic Gradient Descent) and SVM (Support Vector Machine) have been applied on this dataset. From results of experiments, it can be concluded that SVM performs better than NB and LRSGD in terms of accuracy. In case of SVM, an accuracy of 87.22% is achieved.
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Shaukat, Saima, Muhammad Asad, and Asmara Akram. "Developing an Urdu Lemmatizer Using a Dictionary-Based Lookup Approach." Applied Sciences 13, no. 8 (April 19, 2023): 5103. http://dx.doi.org/10.3390/app13085103.
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Lemmatization aims at returning the root form of a word. The lemmatizer is envisioned as a vital instrument that can assist in many Natural Language Processing (NLP) tasks. These tasks include Information Retrieval, Word Sense Disambiguation, Machine Translation, Text Reuse, and Plagiarism Detection. Previous studies in the literature have focused on developing lemmatizers using rule-based approaches for English and other highly-resourced languages. However, there have been no thorough efforts for the development of a lemmatizer for most South Asian languages, specifically Urdu. Urdu is a morphologically rich language with many inflectional and derivational forms. This makes the development of an efficient Urdu lemmatizer a challenging task. A standardized lemmatizer would contribute towards establishing much-needed methodological resources for this low-resourced language, which are required to boost the performance of many Urdu NLP applications. This paper presents a lemmatization system for the Urdu language, based on a novel dictionary lookup approach. The contributions made through this research are the following: (1) the development of a large benchmark corpus for the Urdu language, (2) the exploration of the relationship between parts of speech tags and the lemmatizer, and (3) the development of standard approaches for an Urdu lemmatizer. Furthermore, we experimented with the impact of Part of Speech (PoS) on our proposed dictionary lookup approach. The empirical results showed that we achieved the best accuracy score of 76.44% through the proposed dictionary lookup approach.
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Amanat, Asma, and Ashiq Hussain. "THE URDU AND ENGLISH MEDIUM DIVIDE IN PUNJAB, PAKISTAN." Pakistan Journal of Social Research 03, no. 04 (December 31, 2021): 616–21. http://dx.doi.org/10.52567/pjsr.v3i4.321.
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English and Urdu languages are used in Pakistan as official languages for spoken and written communication. In the education system of Pakistan, a linguistic divide exists, and it divided the Pakistani education system into two streams known as English medium and Urdu medium. In Pakistan, Government schools, colleges, and universities are Urdu medium and offer very low-price education to the poorer and middle-class communities whereas English medium schools, colleges, and Universities are owned by private organizations and offer education to economically well-off societies. The said disparity in the education system created self-identities and linguistic capital. Qualitative methodology and thematic data analysis techniques were used to prepare proper report findings to comprehend how scholars’ experiment and make their own opinions keeping in mind the past and present situations of education viz-a-viz social impact of English language learning. In this study, it is also recommended how inequalities and language discrimination can be removed in the government language policies. Keywords: English, Urdu, English-Urdu divide, English learning, Language challenges.
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Salman, Muhammad, and Syed Muhammad Abouzar Shah Bukhari. "Language Medium Dynamics in Pakistani Education: A Historical Analysis." Knowledge 1, no. 1 (December 30, 2022): 15–24. http://dx.doi.org/10.63062/tk/2k22a.13707.
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Punjabi, Pashto, Sindhi, Siraiki, and Baluchi are Pakistan's main languages. Although Urdu is the national language, English is still spoken in significant areas like higher bureaucracy and the armed forces officer corps, a remnant of British colonialism. This manuscript examines Pakistan's language medium dispute regarding English-only schooling for the privileged before partition. An English-educated Anglicized elite was expected to maintain British rule in their own interests, strengthening the empire. Thus, most provinces taught the masses in Urdu, save Sind, where Sindhi was used. This method produced a cost-effective subordinate workforce. In modern Pakistan, the elite attend exclusive English-medium schools, whereas most other schools, especially in metropolitan Sind, have a large Urdu population and teach in Urdu. The indigenously educated proto-elite, mostly Urdu-trained, opposes this duality and wants Urdu as the medium of education. Their argument is that such a transition will help them rise in power, countering the current preference for English education.
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Sadullayev, Shahjahan, and Dr Muhayya Abdurahmanova. "The Problem Of The Origin Of The Urdu Language And The Extent Of The Influence Of The Arabic And Persian Languages On It." Rashhat-e-Qalam 2, no. 2 (September 15, 2022): 79–84. http://dx.doi.org/10.56765/rq.v2i2.73.
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This article talks about exactly where the Urdu language was born, what stages it went through in its development, the influence of the Arabic and Persian languages and Islamic culture on the Urdu language, and the final scientific conclusions are given.
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Quyyum, Afshan, and Tooba Ahmed. "THE FORM AND FUNCTION OF REDUPLICATION IN ENGLISH AND URDU LANGUAGES: A CROSS LINGUIST STUDY." Pakistan Journal of Social Research 04, no. 01 (March 31, 2022): 461–75. http://dx.doi.org/10.52567/pjsr.v4i1.670.
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The main concentration of this work is to look at the forms and functions of morphological doubling in syntax and it aims at to look at the functions and roles of double questions morphemes of Urdu and to make comparative analysis of Urdu and English languages. There are different types of doublings in English language e.g. adverbs doublings, semantic doubling but question doubling does not exist in English language because it is the unique feature of Urdu language only. Qualitative analysis with purposive sampling approach, with the framework of Lexical Functional grammar (LFG).through the concept of F-Structure from (LFG) theory, double morphemes will be analyzed. For this purpose, data will be collected through document analysis, standard books, articles, published researches, dictionaries and data from common users. 100 sentences, consisting of double morpheme, will be selected and same were put into F-Structure to explore their lexical structure to show the semantic functions in both languages. Simultaneously, the sentences were also analyzed syntactically in order to find out their appropriateness. The study may provide a good level of confidence to develop Urdu National Language processing (UNLP) and enlighten the phenomena that morphological doubling in Urdu used for multiple semantic functions to explore human notions and feelings as compare to any other South Asian Language because Urdu is the only language with per gram. and study will also explore the functional and dynamic aspects of LFG. Keywords: Reduplication, LFG, syntax, Double interrogative morphemes.
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Ahmed, Zahir. "The differences of Semantics of Common Words between Arabic and Urdu and its Impact on the teaching of the Arabic language." Journal of Islamic and Religious Studies 2, no. 1 (June 30, 2017): 43–56. http://dx.doi.org/10.36476/jirs.2:1.06.2017.16.
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Arabic language is a family member of Semitic languages whereas Urdu is the member of Indo-European Languages. The Arabic language though is not from the same language family but amazingly it provides much of its share through alphabets, words with its meanings and pronunciation. These features of both languages have provoked to study it under the contrastive linguistics through semantic study of commonly used words. This research is a semantic study of commonly used words in both languages of different language family along with the applied linguistics in Language teaching. There are large numbers of Arabic words that are used in Urdu language and there are significant numbers of words that are used in different meanings, this change in meaning led to change in semantic field. This research paper also study the effect of semantic change of these words on Arabic Language teaching to the Pakistani students whose native language is Urdu. This study will also reveal the reasons of errors during language learning with the help of semantic study if commonly used words.
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Yasir, Muhammad, Chen Li, and Muhammad Amir Malik. "Urdu Sign Language Reorganization via Artificial Neural Networks." Advances in Science and Technology 105 (April 2021): 263–71. http://dx.doi.org/10.4028/www.scientific.net/ast.105.263.
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Sign languages display the same linguistic characteristics as oral languages and utilize the same language services. Sign language processing solutions provide a communication link for persons with hearing impairments and healthy persons. Without these icons' ability to understand, deaf children experience several challenges in learning social norms and cannot meet adults to exchange knowledge. Parents find it challenging to express their messages to their deaf children and not hear their children. This paper focused on establishing Urdu sign language to reduce the communication barrier between ordinary folks and physically impaired people. The present study observed the Urdu Sign Language in deaf children. In this paper, the process of detecting Urdu sign language alphabets is proposed. All the 37 alphabets are identified by using KNN, ANN, and SVM classifiers. Through these alphabets, the teachers at schools and the parents at home can communicate efficiently with their deaf children. Histogram of Gradient technique is used for feature extraction. Urdu Alphabetic are identified. Maximum accuracy is obtained by using a KNN classifier that was 99, which is a significant contribution. Our proposed results are comparable to the state of the art techniques.
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Akbar, Dr Sumaira, Dr Abdul Aziz Malik, and Dr Rabia Sarfraz. "Services of Radio Pakistan in the Promotion of Urdu Language & Literature." Noor e Tahqeeq 7, no. 03 (September 26, 2023): 19–29. http://dx.doi.org/10.54692/nooretahqeeq.2023.07032021.
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Radio is one of the most amazing and effective inventions of the last century. Radio Pakistan came into being with the independence of Pakistan in 1947. From the very beginning, Radio Pakistan made many efforts for the promotion and development of Urdu language, consciously and unconsciously. Urdu programs were started from Radio Pakistan to acquaint people with Urdu language. Later, Urdu experts were hired to correct the accent and pronunciation of Urdu language. The services of Radio Pakistan are very important in popularizing Urdu poetry through music. Drama is an important genre of literature and radio played an important role in bringing and popularizing Urdu drama to the masses. Many radio dramas of Radio Pakistan were later published in book form and proved to be an important addition to Urdu literature. Another important service of Radio Pakistan in relation to the promotion of Urdu language and literature is the publication of the Urdu radio magazine "Ahang". "Ahang" is the only Urdu magazine of Pakistan which has been continuously published since 1948. In short, services of Radio Pakistan for the promotion of Urdu language and literature have been assessed thoroughly.
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Rasheed, Fahad, Mehmoon Anwar, and Imran Khan. "Detecting Cyberbullying in Roman Urdu Language Using Natural Language Processing Techniques." Pakistan Journal of Engineering and Technology 5, no. 2 (September 19, 2022): 198–203. http://dx.doi.org/10.51846/vol5iss2pp198-203.
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Nowadays, social media platforms are the primary source of public communication and information. Social media platforms have become an integral part of our daily lives, and their user base is rapidly expanding as access is extended to more remote locations. Pakistan has around 71.70 million social media users that utilize Roman Urdu to communicate. With these improvements and the increasing number of users, there has been an increase in digital bullying, often known as cyberbullying. This research focuses on social media users who use Roman Urdu (Urdu language written in the English alphabet) to communicate. In this research, we explored the topic of cyberbullying actions on the Twitter platform, where users employ Roman Urdu as a medium of communication. To our knowledge, this is one of the very few studies that address cyberbullying behavior in Roman Urdu. Our proposed study aims to identify a suitable model for classifying cyberbullying behavior in Roman Urdu. To begin, the dataset was designed by extracting data from twitter using twitter's API. The targeted data was extracted using keywords based on Roman Urdu. The data was then annotated as bully and not-bully. After that, the dataset has been pre-processed to reduce noise, which includes punctuation, stop words, null entries, and duplication removal. Following that, features are extracted using two different methods, Count-Vectorizer and TF-IDF Vectorizer, and a set of ten different learning algorithms including SVM, MLP, and KNN was applied to both types of extracted features based on supervised learning. Support Vector Machine (SVM) performed the best out of the implemented algorithms by both combinations, with 97.8 percent when implemented over the TF-IDF features and 93.4 percent when implemented over the CV features. The proposed mechanism could be helpful for online social apps and chat rooms for the better detection and designing of bully word filters, making safer cyberspace for end users.
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Aftab, Saba, Moeen Khan Zai, and Adeena Aftab. "An Analytical Study of Sociolinguistic Variations in Urdu Language." Advances in Social Behavior Research 3, no. 1 (November 23, 2023): 20–26. http://dx.doi.org/10.54254/2753-7102/3/2023025.
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This paper will talk about the sociolinguistic variations in Urdu Language. It takes account with the interviews that conduct from the various senior citizens of Urdu speakers in Pakistan, each interview base on 4 questions to find out Urdu language variations for this paper. The questions on the value of the Urdu language in todays world, what changes took place in the Urdu language over the period from lexical and dialectical point of view. The interviews were conducted as semi-structured with the use of different modern and simple tools. The study of this paper will be very helpful for the young generation of Pakistan because all the past studies did not solely talk about the sociolinguistics in Urdu language. It guides them to bring their native or national language with original accents and vocabulary which shows their actual culture and purity of Urdu language.
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Ullah, Ashraf, Khair Ullah Khan, Aurangzeb Khan, Sheikh Tahir Bakhsh, Atta Ur Rahman, Sajida Akbar, and Bibi Saqia. "Threatening language detection from Urdu data with deep sequential model." PLOS ONE 19, no. 6 (June 6, 2024): e0290915. http://dx.doi.org/10.1371/journal.pone.0290915.
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The Urdu language is spoken and written on different social media platforms like Twitter, WhatsApp, Facebook, and YouTube. However, due to the lack of Urdu Language Processing (ULP) libraries, it is quite challenging to identify threats from textual and sequential data on the social media provided in Urdu. Therefore, it is required to preprocess the Urdu data as efficiently as English by creating different stemming and data cleaning libraries for Urdu data. Different lexical and machine learning-based techniques are introduced in the literature, but all of these are limited to the unavailability of online Urdu vocabulary. This research has introduced Urdu language vocabulary, including a stop words list and a stemming dictionary to preprocess Urdu data as efficiently as English. This reduced the input size of the Urdu language sentences and removed redundant and noisy information. Finally, a deep sequential model based on Long Short-Term Memory (LSTM) units is trained on the efficiently preprocessed, evaluated, and tested. Our proposed methodology resulted in good prediction performance, i.e., an accuracy of 82%, which is greater than the existing methods.
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Anam, Rimsha, Muhammad Waqas Anwar, Muhammad Hasan Jamal, Usama Ijaz Bajwa, Isabel de la Torre Diez, Eduardo Silva Alvarado, Emmanuel Soriano Flores, and Imran Ashraf. "A deep learning approach for Named Entity Recognition in Urdu language." PLOS ONE 19, no. 3 (March 28, 2024): e0300725. http://dx.doi.org/10.1371/journal.pone.0300725.
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Named Entity Recognition (NER) is a natural language processing task that has been widely explored for different languages in the recent decade but is still an under-researched area for the Urdu language due to its rich morphology and language complexities. Existing state-of-the-art studies on Urdu NER use various deep-learning approaches through automatic feature selection using word embeddings. This paper presents a deep learning approach for Urdu NER that harnesses FastText and Floret word embeddings to capture the contextual information of words by considering the surrounding context of words for improved feature extraction. The pre-trained FastText and Floret word embeddings are publicly available for Urdu language which are utilized to generate feature vectors of four benchmark Urdu language datasets. These features are then used as input to train various combinations of Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Gated Recurrent Unit (GRU), CRF, and deep learning models. The results show that our proposed approach significantly outperforms existing state-of-the-art studies on Urdu NER, achieving an F-score of up to 0.98 when using BiLSTM+GRU with Floret embeddings. Error analysis shows a low classification error rate ranging from 1.24% to 3.63% across various datasets showing the robustness of the proposed approach. The performance comparison shows that the proposed approach significantly outperforms similar existing studies.
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Khattak, Abrar. "اردو میں عربی الفاظ کا املا." Al-Idah | Shaykh Zayed Islamic Centre, University of Peshawar 37, - 2 (January 12, 2020): 85–108. http://dx.doi.org/10.37556/al-idah.037.02.0561.
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Arabic language and literature has influenced Urdu language and literature in terms of fonts, grammar as well as orthography .linguists have different opinions about orthography of Arabic words in Urdu. Some of them hold favorable opinion, some have opined against it, while some of the linguists have maintained a balance point of view in terms of orthography. The holy Qur’an is Arabic and perhaps that is the reason Muslims have spiritual affinity with Arabic. But language also sacred the way religion is? Can we relate languages with religion? Moreover, sociolinguistics cannot be ignored and that linguists provides concrete notions based on based on scientific study of languages.in this article, the author has analyzed and discussed the contradictory debates of different academic and applied in Urdu orthography of Arabic words in Urdu.
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Aftab, Saba, Moeen Khan, and Adeena Aftab. "An Analytical Study of Sociolinguistic Variations in Urdu Language." Communications in Humanities Research 23, no. 1 (December 20, 2023): 7–13. http://dx.doi.org/10.54254/2753-7064/23/20230058.
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This paper will talk about the sociolinguistic variations in Urdu Language. The study uses the qualitative method it takes account of the interviews conducted by the various senior citizens of Urdu speakers in Pakistan, each interview is based on 4 questions to find out Urdu language variations for this paper. The questions on the value of the Urdu language in todays world, what changes took place in the Urdu language over the period from a lexical and dialectical point of view. The interviews were conducted as semi-structured with the use of different modern and simple tools. The study of this paper will be very helpful for the young generation of Pakistan because all the past studies did not solely talk about sociolinguistics in the Urdu language. It guides them to bring their native or national language with original accents and vocabulary which shows their actual culture and purity of Urdu language.
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Khan, H. R., M. A. Hasan, M. Kazmi, N. Fayyaz, H. Khalid, and S. A. Qazi. "A Holistic Approach to Urdu Language Word Recognition using Deep Neural Networks." Engineering, Technology & Applied Science Research 11, no. 3 (June 14, 2021): 7140–45. http://dx.doi.org/10.48084/etasr.4143.
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Urdu is one of the most popular languages in the world. It is a Persianized standard register of the Hindi language with considerable and valuable literature. While digital libraries are constantly replacing conventional libraries, a vast amount of Urdu literature is still handwritten. Digitizing this handwritten literature is essential to preserve it and make it more accessible. Nevertheless, the scarcity of Urdu Optical Character Recognition (OCR) research limits a digital library's scope to a manual document search. The limited research work in this area is mainly due to the complexity of Urdu Script. Unlike the English language, the Urdu writing style is cursive, bidirectional, and character shapes and sizes highly vary depending on their position. Holistic word recognition is found to be a better solution among many other text segmentation techniques as it takes the complete word into account instead of segmenting it explicitly or implicitly. For this project, the data of five different Urdu words were collected for training and testing a convolutional neural network and 96% recognition accuracy was achieved.
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Mustafa, Raza-E., Saima Jamshaid, and Ayesha Fahad. "INFLUENCE OF THE FIRST LANGUAGE ON THE LEARNING OF THE LEXICON OF TWO SECOND LANGUAGES." Pakistan Journal of Social Research 05, no. 01 (March 31, 2023): 17–22. http://dx.doi.org/10.52567/pjsr.v5i01.992.
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The present study analyzes the influence of L1 on the learning of the lexicon of two L2s. While a number of studies have been conducted on the influence of first language on the learning of one second language, little work has been done on the influence of first language on the acquisition of two second languages. The data for the present study was collected from the Pakistani learner of English and Arabic as second languages in a madrassa named Dar-ul-Uloom Mhammadia Ghausia in Gujrat. Cummins’ (1980) model of Common Underlying Proficiency (CUP) and Separate Underlying Proficiency (SUP) was used as the theoretical framework. The data showed that Urdu played a largely facilitative role in the learning of the lexicon of both English and Arabic; however, there was a difference of the degree of facilitation. Due to the inherent similarities between Urdu and Arabic, Urdu played a more facilitative role in the learning of Arabic lexicon; whereas, due to the structural differences between Urdu and English, the former played a less facilitative role. Therefore, the learners found learning English more difficult than learning Arabic and the types of errors they made also proved the same. Keywords: Two Second Languages, L1 Influence, Lexicon, English, Arabic, Urdu.
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Tayaba Waliyat Khan and Dr. Rukhsana Bibi. "The Common Heritage of the Eighteenth Century." Tasdiqتصدیق۔ 4, no. 01 (June 30, 2022): 13–22. http://dx.doi.org/10.56276/tasdiq.v4i01.98.
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Urdu is an ancient Aryan language associated with Sanskrit. Its history in India dates back to about 1500 years ago. The form came into being which met the standard of literature. This is how the evolutionary journey of Urdu began early specimens of Urdu are found in northern India Amir Khosrow has tried his hand at all genres of prose. Urdu language words are often found together. That is why all Urdu and Hindi people recognize him as their poet. He used common sense language in his speech which was very clear language. Therefore it is appropriate that Amir Khosrow has accepted the influence of Punjabi, a Steep, dialect. The great heritage of Urdu is also found in Deccan who worked for the promotion & publication of this language. Therefore, the early impressions of Urdu are ancient. Among the earliest works of prose are Khawaja Ashraf Jahangir's Magazine and Khawaja Banda Nawaz Gesu Daraz's Miraj-e-Aashiqeen. The most important work of the century is Sub Ras. Another name of this book is Qissa Husan-o-Adal. The Urdu language is slowly developing.
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Sattar Malik, Dr Abdul. "The Justification of Urdu Letters with Similar Sounds and Diacritics." Noor e Tahqeeq 8, no. 01 (March 31, 2024): 109–18. http://dx.doi.org/10.54692/nooretahqeeq.2024.08012155.
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Urdu script is derived from the Arabic script but Urdu differs from Arabic in its nature and unlike Arabic some sounds are pronounced like each other. Due to that some experts object to Urdu script and suggest the removal of letters with similar sounds. But the removal of these letters can create many complexities and difficulties which cannot be resolved. These eight specific sounds of Urdu are common to Pakistani languages such as Punjabi, Sindhi, Pashto, Balochi, Kashmiri, and other local languages. How is it possible to exclude these words from all these languages? These sounds are the valuable capital of world languages like Persian and Arabic. With this collaboration, Urdu emerges as a great global and scientific language. By removing these letters, Urdu will suffer a great loss in terms of knowledge. There will be an encounter, which cannot be compensated. In short, this change is not feasible in context with Urdu historical background and present linguistic geographical condition. The Urdu script is non- diacritical in its nature and diacritics in Urdu are not arranged in the same way as in Arabic. However, it is necessary to organize the essential diacritics in the basic textbooks. This article argues and analyses the justification of Urdu letters with similar sounds and diacritics in detail.
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Retta, Ephrem Afele, Richard Sutcliffe, Jabar Mahmood, Michael Abebe Berwo, Eiad Almekhlafi, Sajjad Ahmad Khan, Shehzad Ashraf Chaudhry, Mustafa Mhamed, and Jun Feng. "Cross-Corpus Multilingual Speech Emotion Recognition: Amharic vs. Other Languages." Applied Sciences 13, no. 23 (November 22, 2023): 12587. http://dx.doi.org/10.3390/app132312587.
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In a conventional speech emotion recognition (SER) task, a classifier for a given language is trained on a pre-existing dataset for that same language. However, where training data for a language do not exist, data from other languages can be used instead. We experiment with cross-lingual and multilingual SER, working with Amharic, English, German, and Urdu. For Amharic, we use our own publicly available Amharic Speech Emotion Dataset (ASED). For English, German and Urdu, we use the existing RAVDESS, EMO-DB, and URDU datasets. We followed previous research in mapping labels for all of the datasets to just two classes: positive and negative. Thus, we can compare performance on different languages directly and combine languages for training and testing. In Experiment 1, monolingual SER trials were carried out using three classifiers, AlexNet, VGGE (a proposed variant of VGG), and ResNet50. The results, averaged for the three models, were very similar for ASED and RAVDESS, suggesting that Amharic and English SER are equally difficult. Similarly, German SER is more difficult, and Urdu SER is easier. In Experiment 2, we trained on one language and tested on another, in both directions for each of the following pairs: Amharic↔German, Amharic↔English, and Amharic↔Urdu. The results with Amharic as the target suggested that using English or German as the source gives the best result. In Experiment 3, we trained on several non-Amharic languages and then tested on Amharic. The best accuracy obtained was several percentage points greater than the best accuracy in Experiment 2, suggesting that a better result can be obtained when using two or three non-Amharic languages for training than when using just one non-Amharic language. Overall, the results suggest that cross-lingual and multilingual training can be an effective strategy for training an SER classifier when resources for a language are scarce.
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Akhter, Muhammad Pervez, Zheng Jiangbin, Irfan Raza Naqvi, Mohammed Abdelmajeed, and Muhammad Tariq Sadiq. "Automatic Detection of Offensive Language for Urdu and Roman Urdu." IEEE Access 8 (2020): 91213–26. http://dx.doi.org/10.1109/access.2020.2994950.
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Munshi, Sadaf. "Contact-induced language change in a trilingual context." Diachronica 27, no. 1 (June 2, 2010): 32–72. http://dx.doi.org/10.1075/dia.27.1.02mun.
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This study provides a description and analysis of contact-induced language change in a dialect of Burushaski spoken in Srinagar (India). I present a unique situation in which contact outcomes are reflected via interplay of various sociolinguistic factors involving simultaneous contact with two languages — Kashmiri and Urdu, each affecting the language in a specific way: lexical borrowing from Urdu and structural borrowing from Kashmiri. The effects of contact are examined in a trilingual context where the contact languages are placed in a dominance relationship with Urdu occupying the top of the language hierarchy while Burushaski and Kashmiri are competing at the bottom. Data indicate that lexical borrowing and structural borrowing are two different types of contact phenomena which can occur independently of each other. The two processes are influenced by different sociolinguistic factors which may interact in different ways in different contact situations resulting in different types of contact outcomes.
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Ali, Asad, Qaisar Jabbar, Nazir Ahmad Malik, Humayun Baber Kiani, Zumra Noreen, and Ly Ngoc Toan. "Clausal-Internal Switching in Urdu-English: An Evaluation of the Matrix Language Frame Model." REiLA : Journal of Research and Innovation in Language 3, no. 3 (December 28, 2021): 159–69. http://dx.doi.org/10.31849/reila.v3i3.6774.
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The core of this paper is to employ the Matrix Language Frame (MLF) model on Urdu-English clausal-internal switching to identify whether the Matrix Language Frame model potentially accounts for the bilingual linguistic competence efficiently. For this, a qualitative methodology has been adopted for this study. For empirical evidence, data has been taken from eighty Urdu- English bilinguals within a naturalistic setting after categorizing them into four groups, and each group has 20 participants. After conducting audio-recording through non-participant interviews in an informal setting, the collected data was transcribed. The MLF model posited that two languages are fused in a single Intra-CP of a mixed string. The linearly dominant language is Matrix language (ML) that incorporates only late outsider system morphemes. Odd is Embedded language (EL) that supplies content morphemes satisfying the system morpheme principle (SMP) uniformly and morpheme order principle (MOP). The present study ubiquitously scrutinizes that naturalistic data of Urdu-English bilinguals highlights the innovative results: it predicts that Matrix language (ML) is unidentified in intra-CP, no late outsider system morphemes linearize a code-switched sentence, unparalleled constituent and clausal structure, System Morpheme Principle (SMP) and Morpheme Order Principle (SMP) provides the illegitimate output and computes ungrammatical sentences hence; the Matrix Language Frame model redundantly and inconsistently accounts for Urdu-English naturalistic data and its principles have failed to compute Urdu-English naturalistic data.
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Hassan, Muhammad Naeem Ul. "Urdu Language Translation using LESSA." International Journal of Scientific Research in Computer Science and Engineering 6, no. 5 (October 31, 2018): 36–40. http://dx.doi.org/10.26438/ijsrcse/v6i5.3640.
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Daud, Ali, Wahab Khan, and Dunren Che. "Urdu language processing: a survey." Artificial Intelligence Review 47, no. 3 (June 2, 2016): 279–311. http://dx.doi.org/10.1007/s10462-016-9482-x.
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Muhammad Ikram. "A Research And Comparative Review Of Urdu And Gujri Language And Literature." MAIRAJ 1, no. 1 (February 27, 2023): 8–15. http://dx.doi.org/10.58760/mairaj.v1i1.2.
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There is a deep connection between Urdu and Gujri literature. This linguistic relationship is as deep and close as the relationship between these two languages is not with any other language. As a rule, the depth and commonality of the linguistic relationship between Gujri and Urdu is strikingly similar. Their simple syntactic structures, adverbs, sources, adverbial structures, prefixes, letters, idioms, words, similes, gestures, time words, personal pronouns, basic numbers, descriptive idioms, proverbs, proverbs, storage words. , techniques and closures, structure of sentences, tone and traditions, allusions and signs, and ways of thinking and feeling are common in both languages. Apart from this, the genres of speech, poetry and prose are also common. This paper represents a research and comparative review of Urdu and Gujri language and Literature.
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Mirza, Amna, and Alexandra Gottardo. "The Role of Context in Learning to Read Languages That Use Different Writing Systems and Scripts: Urdu and English." Languages 8, no. 1 (March 16, 2023): 86. http://dx.doi.org/10.3390/languages8010086.
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Language learning involves linguistic and societal factors that interact to facilitate or hinder second language learning. Different contextual factors provide an opportunity to examine and understand the similarities and differences that occur among bilingual children who learn the same first (L1) and second language (L2) in different countries and contexts. This paper explored the role of context, learners’ profiles and linguistic differences of Urdu–English bilinguals in Canada and Pakistan. Within- and cross-linguistic comparisons were conducted for 76 Urdu–English speakers from Pakistan and 50 participants from Canada. Children, ages 8–10 years, were tested on language and literacy measures in both languages. Group comparisons of performance on language measures across languages and countries confirmed that relative strengths were based on the societal languages of each country (Urdu in Pakistan and English in Canada). Despite some similarities in relations among skills within language, differences in the language learning context provided interesting findings regarding the role of L1 skills for acquiring L2 reading skills. These findings challenge the theories developed using data from L2 learners, where learners acquire the societal language in immersion contexts, such as in North America or Europe.
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Muhammad Waseem. "Classifying Urdu Verbs Using Rule Based Approach." Lahore Garrison University Research Journal of Computer Science and Information Technology 5, no. 1 (February 9, 2021): 71–78. http://dx.doi.org/10.54692/lgurjcsit.2021.0501178.
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To make dictionaries complete and to keep their size restricted, there is an approach in the linguistic world to equip these dictionaries with morphological information. This module of morphological information is usually known as a morphological analyzer or morphological classifier, which normally contains the complete possible linguistic information about each word for that particular language and it also describes the rules of derivations from the root of a word and its various inflections, respectively. In this work, a classifier for Urdu verbs (CUV) is proposed which is still a challenging research issue, as Urdu is a language of high inflection and derivation. The available stemmers for Urdu do not provide enough information about inflectional and derivational forms of words. Also, morphological classifiers available for Urdu are not worthy of handling various problems and delivering results that prune errors. In our work, a rule based CUV is designed which is able to classify 63 forms of Urdu verbs successfully out of 66. Available Urdu language processing tools are very rare compared to other higher inflectional languages such as German, Turkish, etc., which have competitive morphological classifiers. However, the studies related to Urdu verb morphological classification are identified and a comparative study is presented in this article. In short, this work is a positive contribution to the community, and it provides sufficient information with promising results specifically on inflectional and derivational forms of Urdu verbs.
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Gul, Sarah, Musarrat Azher, and Sana Nawaz. "Development of Saraiki WordNet by Mapping of Word Senses: A Corpus-based Approach." Linguistics and Literature Review 7, no. 2 (October 29, 2021): 46–66. http://dx.doi.org/10.32350/llr.72/04.
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This paper aimed to develop the Saraiki WordNet. Saraiki is one of the regional languages spoken in Pakistan and has a unique history of its own. Saraiki language is remarkably similar to two languages, namely Punjabi and Sindhi. Saraiki has different dialects and each dialect is representative of the region where it is spoken. This paper used the Urdu WordNet (Zafar, Mahmood, Shams & Hussain, 2014) as the basis for the formation of Saraiki WordNet. Urdu WordNet (Zafar et al., 2014) was created by UET Lahore and is based on Princeton WordNet (Miller, 1990). Dictionaries or lughats and literary sources, such as poetry, fiction, as well as non-literary sources, such as newspapers of Saraiki language, were used to extract data. Additionally, Urdu word senses were mapped onto Saraiki word senses. The method used in this study was mapping, while the expansion approach was used in the mapping process. This study may aid in creating bilingual dictionaries (of Saraiki and Urdu?) in the future.
Keywords: expand approach, mapping, Saraiki language, WordNet
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Muhammad Hassaan Rafiq, Shiza Gul Niazi, and Subaika Ali. "Comparative Analysis of Urdu Based Stemming Techniques." Lahore Garrison University Research Journal of Computer Science and Information Technology 2, no. 3 (September 28, 2018): 11–14. http://dx.doi.org/10.54692/lgurjcsit.2018.020348.
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Stemming reduces many variant forms of a word into its base, stem or root, which is necessary for many different language processing application including Urdu. Urdu is a morphologically rich and resourceful language. Multilingual Urdu words are very challenging to process due to complexity of morphology. The Research of Urdu stemming has an age of a decade. The present work introduces a research on Urdu stemmers with better performance as compare to the existing Urdu stemmer.
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Tuteja, K. L. "‘Hindi–Hindu’ discourse in late colonial Punjab." Studies in People's History 6, no. 1 (May 21, 2019): 33–51. http://dx.doi.org/10.1177/2348448919834776.
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One of the major spheres in which the communal divide in India especially in the north has manifested itself is that of language, around the controversy over Hindi and Urdu. It raged in colonial Punjab as well, despite the fact that neither language was spoken over the larger part of it. In a sense, therefore, it was imported from the then North-Western Provinces (now UP), where the original dialect had given rise to a common language (Khari Boli, Hindustani) with two scripts, around which Hindi and Urdu came to be created as literary languages. Though Urdu remained in colonial times the main print and school language in pre-1947 Punjab, the language controversy continued to play a communally divisive role. In Punjab, the Arya Samaj was the main torchbearer for Hindi, with even nationalists like Lala Lajpat Rai in its camp.
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Rehman, Iffraah, and Tariq Rahim Soomro. "Urdu Sentiment Analysis." Applied Computer Systems 27, no. 1 (June 1, 2022): 30–42. http://dx.doi.org/10.2478/acss-2022-0004.
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Abstract The world is heading towards more modernized and digitalized data and therefore a significant growth is observed in the active number of social media users with each passing day. Each post and comment can give an insight into valuable information about a certain topic or issue, a product or a brand, etc. Similarly, the process to uncover the underlying information from the opinion that a person keeps about any entity is called a sentiment analysis. The analysis can be carried out through two main approaches, i.e., either lexicon-based or machine learning algorithms. A significant amount of work in the different domains has been done in numerous languages for sentiment analysis, but minimal research has been conducted on the national language of Pakistan, which is Urdu. Twitter users who are familiar with Urdu update the tweets in two different textual formats either in Urdu Script (Nastaleeq) or in Roman Urdu. Thus, the paper is an attempt to perform the sentiment analysis on the Urdu language by extracting the tweets (Nastaleeq and Roman Urdu both) from Twitter using Tweepy API. A machine learning-based approach has been adopted for this study and the tool opted for the purpose is WEKA. The best algorithm was identified based on evaluation metrics, which comprise the number of correctly and incorrectly classified instances, accuracy, precision, and recall. SMO was found to be the most suitable machine learning algorithm for performing the sentiment analysis on Urdu (Nastaleeq) tweets, while the Roman Urdu Random Forest algorithm was identified as the best one.
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Dr. Muhammad Gulfraz Abbasi, Dr. Zafar Iqbal Khattak, and Dr. Yasir Arafat. "Pahari Distinctiveness without Pahari Language: A Study of Language Attitudes of the Pahari Community." sjesr 4, no. 2 (May 25, 2021): 325–32. http://dx.doi.org/10.36902/sjesr-vol4-iss2-2021(325-332).
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Pahari language spoken in Murree and its suburbs is in contact with Urdu, the national language of Pakistan. It is also in contact with Punjabi and English. The present study explores the views and attitudes of the Pahari speaking community regarding the Pahari identity and culture vis-à-vis languages like Pahari, Punjabi, Urdu, and English. The study is ethnographic and is based on detailed observation and in-depth interviews of a sample of 91 people belonging to three generations. The study concludes that Pahari speaking community especially the Abbasi tribe, on the whole, claims to protect their culture and identity but gradually each new generation is hesitant in continuing Pahari as the symbol of their identity. As a result, language is, to a great extent, shifting towards Urdu. On a minor level, its shift to English and Punjabi cannot be ignored. The paper also explores certain reasons latent behind this kind of attitude.
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Mahnoor Ikram, Aiman Shahbaz, and Muhammad Shoaib Tahir. "A Comparison of Urdu and Punjabi First language Interference on English as Second Language." Panacea Journal of Linguistics & Literature 2, no. 2 (February 12, 2024): 334–43. http://dx.doi.org/10.59075/pjll.v2i2.346.
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This study examines errors in ESL students focusing on those who speak Urdu and Punjabi as their first languages. It uses Optimality Theory (OT) as a framework to explore the interaction between markedness and faithfulness constraints within OT. The study employs a mixed methods approach, including surveys and audio recordings from 30 participants (15 Urdu speakers and 15 Punjabi speakers). Three phonological factors are investigated; stress patterns, pronunciation of interdental /th/ and differentiation between bilabial /w/ and labiodental /v/. The data analysis, presented through bar graphs and interpreted using OT reveals nuanced patterns of errors. Notably Punjabi L1 speakers demonstrate a frequency of mistakes suggesting impact from their first language. This research significantly contributes to understanding the dynamics of language interference by shedding light on how phonological differences, among Urdu, Punjabi and English influence specific pronunciation errors. The findings hold educational ramifications for ESL teachers looking to upgrade language instructions custom-made to the phonological backgrounds of their students.
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Gribanova, Vera, and Emily Manetta. "Ellipsis in Wh-in-Situ Languages: Deriving Apparent Sluicing in Hindi-Urdu and Uzbek." Linguistic Inquiry 47, no. 4 (October 2016): 631–68. http://dx.doi.org/10.1162/ling_a_00225.
Full textAbstract:
Wh-in-situ languages have a special role to play in investigating the relation between the wh-syntax of a language and the availability of sluicing-like constructions (SLCs). Van Craenenbroeck and Lipták (2013) propose that whether a language exhibits genuine sluicing should be predictable from the syntax of the language’s wh-questions in nonelliptical contexts. We refine this formulation by considering SLCs in two contrasting wh-in-situ languages, Hindi-Urdu and Uzbek. Hindi-Urdu wh-movement occurs in the narrow syntax, but is obscured by PF processes; in Uzbek, no narrow syntax dependency is involved. Correspondingly, only Hindi-Urdu SLCs involve genuine sluicing; Uzbek SLCs are derived from reduced copular clauses. Thus, narrow syntax wh-movement may be obscured by lower-copy pronunciation in nonelliptical environments; the head of the wh-chain is then pronounced in combination with ellipsis, but not otherwise. Here, we demonstrate that the availability of genuine sluicing in Hindi-Urdu and Uzbek corresponds directly to the specific properties of their wh-systems, but not necessarily to the surface position of wh-material in a typical constituent question.