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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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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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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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JAFAR, MUHAMMAD RAHIM. "Impact of different factors affecting Urdu teaching in Pakistan: A Confirmatory Factor." Journal of Social Sciences and Economics 2, no. 1 (April 13, 2023): 26–34. http://dx.doi.org/10.61363/jsse.v2i1.69.
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In Pakistani society, Urdu is widely recognized as the official language of the country as well as one of the widely spoken languages. Urdu is regarded as one of the symbols of national and cultural identity and plays an important role in social life. This study used CFA to examine whether three factors in Urdu teaching (curriculum and teaching materials, teachers and teaching methods, and learning environment) had a significant impact on Urdu teaching. Confirmatory Factor Analysis (CFA) is a multivariate statistical method designed to verify whether a set of potential factors proposed by researchers can explain the variation in observed variables. CFA was used in this study to build a three-factor model that includes three factors: curriculum and teaching materials, teachers and teaching methods, and learning environment. The study will use sample data to perform parameter estimates of the model and use model fit metrics (fit index and standardized residuals) to assess how well the model fits.
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Akram, Dr Muhammad, and Dr Ayesha Qurrat ul Ain. "The Impact of the Partition of India on the Study of Hinduism in the Urdu Language." ĪQĀN 2, no. 04 (June 30, 2020): 69–86. http://dx.doi.org/10.36755/iqan.v2i04.147.
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Religion, language, and race have been among the most crucial factors behind the formation of various national and communal identities in modern South Asian history. Just like the political division of British India, the complex interplay of these factors also culminated in a bifurcation of linguistic boundaries along the religious lines according to which Urdu became associated with Islam and Muslims. In contrast, Hindi became increasingly connected to the Hindu culture. These historical developments also affected the extent and nature of the academic materials on Hinduism in the Urdu language, which the present paper examines. The paper takes stock of different relevant materials. Then, it discusses how the changed socio-political realities quantitatively and qualitatively affected the works on Hinduism in the Urdu language as the majority of the Hindu scholars lost enthusiasm to write on their religion in Urdu considering its increased perception of being a Muslim language. Muslims in Pakistan, on the other hand, lost opportunities of everyday interaction with Hindus and easy access to the original Hindi and Sanskrit sources resulting in a considerable decline in Hindu studies on their part. Thus, the overall production of literature on Hinduism in the Urdu language declined sharply. By implication, the paper hints at how decisively socio-political and historical contexts bear on the pursuit of the academic study of religion.
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Kottacheruvu, Nagendra. "Developing Writing Skills through English Short Stories: A Case Study in the Classroom." International Journal of Language and Literary Studies 5, no. 1 (April 3, 2023): 287–99. http://dx.doi.org/10.36892/ijlls.v5i1.1243.
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This study seeks to determine the efficacy and utility of teaching writing skills through short stories to third-semester postgraduate students whose native language and language of instruction is Urdu at Maulana Azad National Urdu University in Hyderabad, India. This article investigates primarily the extent to which selected English short stories are useful and effective for teaching English writing skills. Due to their Urdu-influenced origins, it is a fact that the majority of our students struggle to speak and write in English. Due to their socio-cultural, fiscal, and pedagogical circumstances, as well as the way they are taught, they rarely interact with the target language. They are always hesitant to speak and write in the target language due to fear, hesitancy, and lack of experience, despite their passion for learning English. Mastering writing is regarded as one of the most transferable skills because it requires an extensive vocabulary and correct grammar. In addition, it requires constant effort, practise, reading, and exposure to language use. Students from both Madarasa and Urdu backgrounds with little exposure and practise find mastering writing to be the most challenging endeavour. The findings of this study indicate that reading English short stories improves writing skills.
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Khan, Wahab, Ali Daud, Khurram Shahzad, Tehmina Amjad, Ameen Banjar, and Heba Fasihuddin. "Urdu Named Entity Recognition Using Conditional Random Fields." Applied Sciences 12, no. 13 (June 23, 2022): 6391. http://dx.doi.org/10.3390/app12136391.
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Named entity recognition (NER) is an important task in natural language processing, as it is widely featured as a key information extraction sub-task with numerous application areas. A plethora of attempts was made for NER detection in Western and Asian languages. However, little effort has been made to develop techniques for the Urdu language, which is a prominent South Asian language with hundreds of millions of speakers across the globe. NER in Urdu is considered a hard problem owing to several reasons, including the paucity of large, annotated datasets; an inaccurate tokenizer; and the absence of capitalization in the Urdu language. To this end, this study proposed a conditional-random-field-based technique with both language-dependent and language-independent features, such as part-of-speech tags and context windows of words, respectively. As a second contribution, we developed an Urdu NER dataset (UNER-I) in which a large number of NE types were manually annotated. To evaluate the effectiveness of the proposed approach, as well as the usefulness of the dataset, experiments were performed using the dataset we developed and an existing dataset. The results of the experiments showed that our proposed technique outperformed the baseline technique for both datasets by improving the F1 scores by 1.5% to 3%. Furthermore, the results demonstrated that the enhanced dataset was useful for learning and prediction in a supervised learning approach.
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Khan, Muzammil, Kifayat Ullah, Yasser Alharbi, Ali Alferaidi, Talal Saad Alharbi, Kusum Yadav, Naif Alsharabi, and Aakash Ahmad. "Understanding the Research Challenges in Low-Resource Language and Linking Bilingual News Articles in Multilingual News Archive." Applied Sciences 13, no. 15 (July 25, 2023): 8566. http://dx.doi.org/10.3390/app13158566.
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The developed world has focused on Web preservation compared to the developing world, especially news preservation for future generations. However, the news published online is volatile because of constant changes in the technologies used to disseminate information and the formats used for publication. News preservation became more complicated and challenging when the archive began to contain articles from low-resourced and morphologically complex languages like Urdu and Arabic, along with English news articles. The digital news story preservation framework is enriched with eighteen sources for Urdu, Arabic, and English news sources. This study presents challenges in low-resource languages (LRLs), research challenges, and details of how the framework is enhanced. In this paper, we introduce a multilingual news archive and discuss the digital news story extractor, which addresses major issues in implementing low-resource languages and facilitates normalized format migration. The extraction results are presented in detail for high-resource languages, i.e., English, and low-resource languages, i.e., Urdu and Arabic. LRLs encountered a high error rate during preservation compared to high-resource languages (HRLs), corresponding to 10% and 03%, respectively. The extraction results show that few news sources are not regularly updated and release few new news stories online. LRLs require more detailed study for accurate news content extraction and archiving for future access. LRLs and HRLs enrich the digital news story preservation (DNSP) framework. The Digital News Stories Archive (DNSA) preserves a huge number of news articles from multiple news sources in LRLs and HRLs. This paper presents research challenges encountered during the preservation of Urdu and Arabic-language news articles to create a multilingual news archive. The second part of the paper compares two bilingual linking mechanisms for Urdu-to-English-language news articles in the DNSA: the common ratio measure for dual language (CRMDL) and the similarity measure based on transliteration words (SMTW) with the cosine similarity measure (CSM) baseline technique. The experimental results show that the SMTW is more effective than the CRMDL and CSM for linking Urdu-to-English news articles. The precision improved from 46% and 50% to 60%, and the recall improved from 64% and 67% to 82% for CSM, CRMDL, and SMTW, respectively, with improved impact of common terms as well.
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Aiman, Aisha, Yao Shen, Malika Bendechache, Irum Inayat, and Teerath Kumar. "AUDD: Audio Urdu Digits Dataset for Automatic Audio Urdu Digit Recognition." Applied Sciences 11, no. 19 (September 23, 2021): 8842. http://dx.doi.org/10.3390/app11198842.
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The ongoing development of audio datasets for numerous languages has spurred research activities towards designing smart speech recognition systems. A typical speech recognition system can be applied in many emerging applications, such as smartphone dialing, airline reservations, and automatic wheelchairs, among others. Urdu is a national language of Pakistan and is also widely spoken in many other South Asian countries (e.g., India, Afghanistan). Therefore, we present a comprehensive dataset of spoken Urdu digits ranging from 0 to 9. Our dataset has 25,518 sound samples that are collected from 740 participants. To test the proposed dataset, we apply different existing classification algorithms on the datasets including Support Vector Machine (SVM), Multilayer Perceptron (MLP), and flavors of the EfficientNet. These algorithms serve as a baseline. Furthermore, we propose a convolutional neural network (CNN) for audio digit classification. We conduct the experiment using these networks, and the results show that the proposed CNN is efficient and outperforms the baseline algorithms in terms of classification accuracy.
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Afzal, Nimra, Shoaib Waqas, Muhammad Tariq, Asifa Javaid, and Hafiz Muhammad Asim. "Translation and Validation Scale for Assessment and Rating of Ataxia in Urdu Language for Cerebral Palsy Patients." Pakistan Journal of Medical and Health Sciences 16, no. 9 (September 30, 2022): 58–59. http://dx.doi.org/10.53350/pjmhs2216958.
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Aim: To translate the Scale for assessment and rating of Ataxia from English to Urdu language Methods: The study employed a linguistic validation study design with a non-random sample approach and was done at different clinical setups of Lahore. Parents of children with ataxic cerebral palsy with children aged 2 to 15 years old who speak Urdu should contact us. Sara's English version was translated into Urdu by two translators, one with a medical background and the other with a technical background in Urdu, both proficient in Urdu and English. Two individuals with medical and technology backgrounds who are competent in Urdu to English translation reverse translated the translated versions of SARA-Urdu I and SARA-Urdu II into English. The re-translated versions of SARA-Urdu I and SARA-Urdu II were translated back into English (SARA English III and SARA English IV). The translated versions were compared and generated a new Urdu version SARA Urdu-V. The data was entered into the SPSS version 23 application, which was also used to analyze it. Results: The translated version of the SARA scale has a Cronbach's alpha of 0.883. The inter-item correlation between the total SARA score and the eight domains of gait, stance, sitting, speech disturbance, finger chase, nose finger test, fast alternating hand movements, and heel shin slide was 0.131, 0.046, 0.159, 0.188, 0.136, 0.400, 0.698, and 0.450, respectively, after the translation of the Urdu version of SARA. For test retest reliability, the Pearson correlation value varied from 0.400 to 0.842. Conclusion: The Urdu version of SARA has appropriate internal consistency and fair inter-item correlation, and hence may be utilized by Urdu speakers. Keywords: Cerebral palsy, Cerebellar ataxia, Scale for assessment and rating of Ataxia
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Khan, Muzammil, Sarwar Shah Khan, Yasser Alharbi, Ali Alferaidi, Talal Saad Alharbi, and Kusum Yadav. "The Role of Transliterated Words in Linking Bilingual News Articles in an Archive." Applied Sciences 13, no. 7 (March 31, 2023): 4435. http://dx.doi.org/10.3390/app13074435.
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Retrieving a specific digital information object from a multi-lingual huge and evolving news archives is challenging and complicated against a user query. The processing becomes more difficult to understand and analyze when low-resourced and morphologically complex languages like Urdu and Arabic scripts are included in the archive. Computing similarity against a query and among news articles in huge and evolving collections may be inaccurate and time-consuming at run time. This paper introduces a Similarity Measure based on Transliteration Words (SMTW) from the English language in the Urdu scripts for linking news articles extracted from multiple online sources during the preservation process. The SMTW link Urdu-to-English news articles using an upgraded Urdu-to-English lexicon, including transliteration words. The SMTW was exhaustively evaluated to assess the effectiveness using different size datasets and the results were compared with the Common Ratio Measure for Dual Language (CRMDL). The experimental results show that the SMTW was more effective than the CRMDL for linking Urdu-to-English news articles. The precision improved from 50% to 60%, recall improved from 67% to 82%, and the impact of common terms also improved.
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Meher-un-Nisa and Junaid Sarfraz Khan. "Validation of Urdu Translation of DREEM Inventory in a Medical College of Lahore." BioMedica 36, no. 1 (March 31, 2020): 65–69. http://dx.doi.org/10.24911/biomedica/5-156.
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<p><strong>Background and Objective:</strong> Measurement of learning environment is a big challenge in medical education due to complex nature of educational environment such as interaction between students and teachers, learning venue, use of multimedia and other modalities. Introduced in 1997, Dundee Ready Educational Environment Measure (DREEM) is claimed to be a cultural free tool to measure educational environment at undergraduate level. DREEM has been translated and validated in different languages but no study has reported DREEM translation and validation in Urdu Language. This study was carried out to determine validity of Urdu translation of DREEM inventory at an undergraduate medical college in Lahore.<br /><strong>Methods:</strong> This cross-sectional study was carried out at University of Health Sciences Lahore and Fatima Jinnah Medical College Lahore over 2 years (2015-2016) after approval by Institutional Review Board of University of Health Sciences Lahore. Data was collected from 325 undergraduate students using survey method. Urdu translation of DREEM was done by two experts using computer program in page Urdu 2013. Firstly, DREEM questionnaire in English was filled by the participant students. After two weeks, DREEM questionnaire in Urdu was filled by the same students. The DREEM scores in English and Urdu were comparedby applying paired t-test.<br /><strong>Results:</strong> There is no significant difference (P > 0.05) between the DREEM scores in English and Urdu. Thereliability index between 0.7-0.9 was recorded.<br /><strong>Conclusion</strong>: DREEM Inventory has the same validity in Urdu at undergraduate level as in English.</p>
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Umar, Sanober. "The Identity of Language and the Language of Erasure." CASTE / A Global Journal on Social Exclusion 1, no. 1 (February 14, 2020): 175–99. http://dx.doi.org/10.26812/caste.v1i1.29.
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Perhaps it is best to summarize what this article is not about, and then highlight what it seeks to do instead, finally surmising those strands together cohesively. This article is not on Urdu as a medium for self-fashioning elite Ashrafi Muslims in Lucknow who lamented the “death of the city” in shahr-i-adab (the city of high culture and noble manners) kind of literatures, instead it is about how Ashrafis came to be normatively portrayed by prominent leaders of the Congress in Uttar Pradesh as “foreigners.” This article is not exclusively about caste politics, but rather how the trope of the foreigner was used as a way to otherize and prevent some of the most downtrodden Muslims from availing affirmative action policies and how lower caste and Dalit Muslims themselves tried to find liberation away from their stigmatized caste histories, unfortunately without success as conversion did not eclipse casteist tropes against them. This article is not just about the institutional history of the fall of Urdu in Uttar Pradesh, but it focusses on how Urdu was used to shape the minority citizen status of Muslims, and how it impacted their political economy and caste histoies in Lucknow by using both written materials documenting these issues and oral testimonies of Ashrafi and Pasmanda Muslims in Lucknow. In the process, this article is about the contours that defined the production of Muslim minoritysm in India, externally by Post Colonial governmentality of the 1950s and internally by Muslims themselves who were compelled to “self homogenize” despite political and social fractures within the community in the face of demonizing and ahistoric stereotypes of the Muslim community as “backward Musalmaans” that ignored their multiple layers of institutionally created marginalization.
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Dewani, Amirita, Mohsin Ali Memon, Sania Bhatti, Adel Sulaiman, Mohammed Hamdi, Hani Alshahrani, Abdullah Alghamdi, and Asadullah Shaikh. "Detection of Cyberbullying Patterns in Low Resource Colloquial Roman Urdu Microtext using Natural Language Processing, Machine Learning, and Ensemble Techniques." Applied Sciences 13, no. 4 (February 5, 2023): 2062. http://dx.doi.org/10.3390/app13042062.
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Social media platforms have become a substratum for people to enunciate their opinions and ideas across the globe. Due to anonymity preservation and freedom of expression, it is possible to humiliate individuals and groups, disregarding social etiquette online, inevitably proliferating and diversifying the incidents of cyberbullying and cyber hate speech. This intimidating problem has recently sought the attention of researchers and scholars worldwide. Still, the current practices to sift the online content and offset the hatred spread do not go far enough. One factor contributing to this is the recent prevalence of regional languages in social media, the dearth of language resources, and flexible detection approaches, specifically for low-resource languages. In this context, most existing studies are oriented towards traditional resource-rich languages and highlight a huge gap in recently embraced resource-poor languages. One such language currently adopted worldwide and more typically by South Asian users for textual communication on social networks is Roman Urdu. It is derived from Urdu and written using a Left-to-Right pattern and Roman scripting. This language elicits numerous computational challenges while performing natural language preprocessing tasks due to its inflections, derivations, lexical variations, and morphological richness. To alleviate this problem, this research proposes a cyberbullying detection approach for analyzing textual data in the Roman Urdu language based on advanced preprocessing methods, voting-based ensemble techniques, and machine learning algorithms. The study has extracted a vast number of features, including statistical features, word N-Grams, combined n-grams, and BOW model with TFIDF weighting in different experimental settings using GridSearchCV and cross-validation techniques. The detection approach has been designed to tackle users’ textual input by considering user-specific writing styles on social media in a colloquial and non-standard form. The experimental results show that SVM with embedded hybrid N-gram features produced the highest average accuracy of around 83%. Among the ensemble voting-based techniques, XGboost achieved the optimal accuracy of 79%. Both implicit and explicit Roman Urdu instances were evaluated, and the categorization of severity based on prediction probabilities was performed. Time complexity is also analyzed in terms of execution time, indicating that LR, using different parameters and feature combinations, is the fastest algorithm. The results are promising with respect to standard assessment metrics and indicate the feasibility of the proposed approach in cyberbullying detection for the Roman Urdu language.
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Omer, Aatika Khalid, Shoaib Waqas, Muhammad Tariq, Hassan Bin Akram, Muhammad Waqas Mughul, and Somia Faisal. "Translation and Validation of FLACC scale in Urdu Language." Pakistan Journal of Medical and Health Sciences 17, no. 8 (August 30, 2023): 2–4. http://dx.doi.org/10.53350/pjmhs20231782.
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Aim: To translate and validate FLACC scale in Urdu language Methods: At the Ghurki Trust and Teaching Hospital (GTTH), cross-cultural linguistic validation research using non-probability convenient sampling was carried out for 7 months, from July 2021 to January 2022. Two native Urdu speakers with sound English language understanding, one from medical background and second from educational background translated the English FLACC scale. Two English-certified linguists who did not have access to the English version subsequently reverse-translated these two versions into English. These Urdu translations and back translations were critically analyzed and reviewed by a committee of paediatric physical therapists and paediatric clinical practitioners, and a final Urdu version was prepared. After approval of the final translation, this Urdu FLACC scale was applied in the post-operative paediatric population to assess its validity and reliability. After 2 hours, bilingual subjects were administered the English version, while others were again assessed with the Urdu FLACC scale to check linguistic interchangeability and test-retest reliability. Informed consent was taken and documented as well; this study was approved by the Ethical Review Board of Lahore Medical and Dental College, Lahore, Punjab, Pakistan. SPSS version 26 was used for data entry and as well as analysis. Inter-rater reliability was evaluated by using Intraclass correlation coefficients, which determines the strength of association and measure of chance-corrected agreement. The construct validity of the FLACC tool was evaluated by using ABC of content validation and content Validity Index Calculation. Results: The mean age and standard deviation of patients was 5.333+1.5599. The ABC of Content Validation Index, which yielded an average proportion of 0.97. The Cronbach’s alpha of translated FLACC scale is 0.701 when applied on population. Intraclass correlation coefficient ranged from 0.319-0.701 with acceptable reliability. Conclusion: The FLACC scale's translated Urdu version shows good validity and reliability. Key terms: Consolability, Pain, Preverbal population, Validity, Reliability, neonatal ICU
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Mushtaq, Sadia, Muzammil Haider, and Nayyer Hassan. "INFLUENCE OF MOTHER TONGUE ON DEVELOPMENT OF L2 WRITING SKILLS AMONG MIDDLE-SCHOOL STUDENTS." SEPTEMBER 39, no. 03 (September 29, 2023): 369–80. http://dx.doi.org/10.51380/gujr-39-03-09.
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Learning another language which is crucial for academic and professional purposes has been an important focus of research. While learning second language, certain forces related to the language affect this process. One of those forces is the interest of this study. Thus, current study investigates how the mother tongue affects students writing abilities, who are taking English as a compulsory subject in middle school whose native languages are Urdu and Punjabi. Without language, education process in classroom would not be possible. Students experience difficulties in native language when speaking and writing English due to interference. Current research focuses on influence of mother tongue on Pakistani pupils' development of writing skills while studying English as compulsory subject in the classroom. A random sample of 50 pupils in grades 6, 7, & 8 aged amid 11-14 years was chosen from 3 schools, all speaking Urdu & Punjabi as their mother tongues. The Contrastive Analysis Model developed by Robert Lado (1957), proposed by Ellis (1985) was used to analyse data. Results reveal that errors in word order, grammar, & spelling were caused by L1's interference in pupils' writing in target language. Findings suggest that teachers should do the need analysis of the students at beginning of sessions with help of relevant and appropriate tools.
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Shams, Sana, and Muhammad Aslam. "Improving User Intent Detection in Urdu Web Queries with Capsule Net Architectures." Applied Sciences 12, no. 22 (November 21, 2022): 11861. http://dx.doi.org/10.3390/app122211861.
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Detecting the communicative intent behind user queries is critically required by search engines to understand a user’s search goal and retrieve the desired results. Due to increased web searching in local languages, there is an emerging need to support the language understanding for languages other than English. This article presents a distinctive, capsule neural network architecture for intent detection from search queries in Urdu, a widely spoken South Asian language. The proposed two-tiered capsule network utilizes LSTM cells and an iterative routing mechanism between the capsules to effectively discriminate diversely expressed search intents. Since no Urdu queries dataset is available, a benchmark intent-annotated dataset of 11,751 queries was developed, incorporating 11 query domains and annotated with Broder’s intent taxonomy (i.e., navigational, transactional and informational intents). Through rigorous experimentation, the proposed model attained the state of the art accuracy of 91.12%, significantly improving upon several alternate classification techniques and strong baselines. An error analysis revealed systematic error patterns owing to a class imbalance and large lexical variability in Urdu web queries.
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Hassan Kumhar, Sajadul, Syed Immamul Ansarullah, Akber Abid Gardezi, Shafiq Ahmad, Abdelaty Edrees Sayed, and Muhammad Shafiq. "Translation of English Language into Urdu Language Using LSTM Model." Computers, Materials & Continua 74, no. 2 (2023): 3899–912. http://dx.doi.org/10.32604/cmc.2023.032290.
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Sievers, Gianni. "Learning How to Print in Colonial North India: The Nizami Press in Budaun and the First Urdu Manual on the Art of Lithography." Philological Encounters 8, no. 1 (March 16, 2023): 73–109. http://dx.doi.org/10.1163/24519197-bja10038.
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Abstract This article centers on an Urdu-language manual on lithography, published in 1924 by the Nizami Press in Budaun (United Provinces), to explore how a Muslim printer-publisher in a North Indian qaṣbah tried to reform educational methods in his trade. It introduces the Nizami Press (est. 1905) and compares the manual with similar European and Indian instructional handbooks. How did Indian printers and publishers learn their craft? What were the tools and materials used for lithographic printing in colonial India? And given the popularity of lithography, why were such manuals rarely published in Indian languages? By examining the material and technical aspects of the lithographic printing process explained in the Urdu manual, this article engages with larger scholarly debates revolving around knowledge production, pedagogy, and technological developments in South Asia. Furthermore, it analyzes the manual’s language to demonstrate how printers and publishers were engaged in discourses about nationalism, modernization, and social reform.
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Pervaiz, Azhar, Abdul Ghaffar Ikram, Naima Batool, and Sadia Saeed. "ACQUISITION OF WH-QUESTIONS BY SECOND LANGUAGE SPEAKERS OF ENGLISH IN PAKISTAN." Humanities & Social Sciences Reviews 9, no. 3 (June 21, 2021): 1078–88. http://dx.doi.org/10.18510/hssr.2021.93107.
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Purpose of the study: The purpose of the current study is to investigate the acquisition of Wh-questions of English by Urdu L1 speakers in Pakistan. Acquisition of different syntactic structures has been an attractive area of interest for the scholars working in the area of second language acquisition. The study draws on approaches of Universal Grammar (UG) and Second Language Acquisition (SLA). The researchers aim at finding out whether the second language is acquired in the same way as the first language or not. Both Urdu and English allow Wh-questions formation but the placement of the Wh-word is completely at a different position. Urdu is an in-situ language that does not allow Movement of the Wh-word, and English allows the Movement of the Wh-word. So, this study highlights whether speakers of Urdu can acquire the structures of Wh-questions or not.
Methodology: The study uses a mixed-method research design, and the data was collected from the speakers of Urdu who speak it as their native language in order to draw the findings. The current research employs a questionnaire that is divided into two parts: elicitation task and grammatical judgement task. For the elicitation task, the students were provided with the statements with the underlined words of which they had to form Wh-questions and for the second, a task was designed on the basis of the lickert scale and it was designed to judge the grammar of the students. The population of this study is limited to speakers of Urdu who speak English as their second language and the sample was selected from the vicinity of Sargodha city of Pakistan.
Main Findings: The results of this mixed-method study reveal that students face problems while forming and identifying Wh-questions, despite compulsory education in English. The findings of the current study supported the partial access hypothesis.
Applications of this study: The study is very important in the area of second language acquisition and informs how the speakers of the English language as a second language acquire the Wh-question structure. The study can be applied in designing teaching materials for the learners of English as a second language besides informing the language software modulation in order to ease the language learning process.
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Umair, Muhammad, Muhammad Zubair, Farhan Dawood, Sarim Ashfaq, Muhammad Shahid Bhatti, Mohammad Hijji, and Abid Sohail. "A Multi-Layer Holistic Approach for Cursive Text Recognition." Applied Sciences 12, no. 24 (December 9, 2022): 12652. http://dx.doi.org/10.3390/app122412652.
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Urdu is a widely spoken and narrated language in several South-Asian countries and communities worldwide. It is relatively hard to recognize Urdu text compared to other languages due to its cursive writing style. The Urdu text script belongs to a non-Latin cursive family script like Arabic, Hindi and Chinese. Urdu is written in several writing styles, among which ‘Nastaleeq’ is the most popular and widely used font style. A gap still poses a challenge for localization/detection and recognition of Urdu Nastaleeq text as it follows modified version of Arabic script. This research study presents a methodology to recognize and classify Urdu text in Nastaleeq font, regardless of the text position in the image. The proposed solution is comprised of a two-step methodology. In the first step, text detection is performed using the Connected Component Analysis (CCA) and Long Short-Term Memory Neural Network (LSTM). In the second step, a hybrid Convolution Neural Network and Recurrent Neural Network (CNN-RNN) architecture is deployed to recognize the detected text. The image containing Urdu text is binarized and segmented to produce a single-line text image fed to the hybrid CNN-RNN model, which recognizes the text and saves it in a text file. The proposed technique outperforms the existing ones by achieving an overall accuracy of 97.47%.
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Zahid, Hira, Munaf Rashid, Samreen Hussain, Fahad Azim, Sidra Abid Syed, and Afshan Saad. "Recognition of Urdu sign language: a systematic review of the machine learning classification." PeerJ Computer Science 8 (February 18, 2022): e883. http://dx.doi.org/10.7717/peerj-cs.883.
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Background and Objective Humans communicate with one another using language systems such as written words or body language (movements), hand motions, head gestures, facial expressions, lip motion, and many more. Comprehending sign language is just as crucial as learning a natural language. Sign language is the primary mode of communication for those who have a deaf or mute impairment or are disabled. Without a translator, people with auditory difficulties have difficulty speaking with other individuals. Studies in automatic recognition of sign language identification utilizing machine learning techniques have recently shown exceptional success and made significant progress. The primary objective of this research is to conduct a literature review on all the work completed on the recognition of Urdu Sign Language through machine learning classifiers to date. Materials and methods All the studies have been extracted from databases, i.e., PubMed, IEEE, Science Direct, and Google Scholar, using a structured set of keywords. Each study has gone through proper screening criteria, i.e., exclusion and inclusion criteria. PRISMA guidelines have been followed and implemented adequately throughout this literature review. Results This literature review comprised 20 research articles that fulfilled the eligibility requirements. Only those articles were chosen for additional full-text screening that follows eligibility requirements for peer-reviewed and research articles and studies issued in credible journals and conference proceedings until July 2021. After other screenings, only studies based on Urdu Sign language were included. The results of this screening are divided into two parts; (1) a summary of all the datasets available on Urdu Sign Language. (2) a summary of all the machine learning techniques for recognizing Urdu Sign Language. Conclusion Our research found that there is only one publicly-available USL sign-based dataset with pictures versus many character-, number-, or sentence-based publicly available datasets. It was also concluded that besides SVM and Neural Network, no unique classifier is used more than once. Additionally, no researcher opted for an unsupervised machine learning classifier for detection. To the best of our knowledge, this is the first literature review conducted on machine learning approaches applied to Urdu sign language.
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Mehmood, Aneela, Muhammad Shoaib Farooq, Ansar Naseem, Furqan Rustam, Mónica Gracia Villar, Carmen Lili Rodríguez, and Imran Ashraf. "Threatening URDU Language Detection from Tweets Using Machine Learning." Applied Sciences 12, no. 20 (October 14, 2022): 10342. http://dx.doi.org/10.3390/app122010342.
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Technology’s expansion has contributed to the rise in popularity of social media platforms. Twitter is one of the leading social media platforms that people use to share their opinions. Such opinions, sometimes, may contain threatening text, deliberately or non-deliberately, which can be disturbing for other users. Consequently, the detection of threatening content on social media is an important task. Contrary to high-resource languages like English, Dutch, and others that have several such approaches, the low-resource Urdu language does not have such a luxury. Therefore, this study presents an intelligent threatening language detection for the Urdu language. A stacking model is proposed that uses an extra tree (ET) classifier and Bayes theorem-based Bernoulli Naive Bayes (BNB) as the based learners while logistic regression (LR) is employed as the meta learner. A performance analysis is carried out by deploying a support vector classifier, ET, LR, BNB, fully connected network, convolutional neural network, long short-term memory, and gated recurrent unit. Experimental results indicate that the stacked model performs better than both machine learning and deep learning models. With 74.01% accuracy, 70.84% precision, 75.65% recall, and 73.99% F1 score, the model outperforms the existing benchmark study.
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Bhatti, Aamna, Ameera Arif, Waqar Khalid, Baber Khan, Ahmad Ali, Shehzad Khalid, and Atiq ur Rehman. "Recognition and Classification of Handwritten Urdu Numerals Using Deep Learning Techniques." Applied Sciences 13, no. 3 (January 27, 2023): 1624. http://dx.doi.org/10.3390/app13031624.
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Urdu is a complex language as it is an amalgam of many South Asian and East Asian languages; hence, its character recognition is a huge and difficult task. It is a bidirectional language with its numerals written from left to right while script is written in opposite direction which induces complexities in the recognition process. This paper presents the recognition and classification of a novel Urdu numeral dataset using convolutional neural network (CNN) and its variants. We propose custom CNN model to extract features which are used by Softmax activation function and support vector machine (SVM) classifier. We compare it with GoogLeNet and the residual network (ResNet) in terms of performance. Our proposed CNN gives an accuracy of 98.41% with the Softmax classifier and 99.0% with the SVM classifier. For GoogLeNet, we achieve an accuracy of 95.61% and 96.4% on ResNet. Moreover, we develop datasets for handwritten Urdu numbers and numbers of Pakistani currency to incorporate real-life problems. Our models achieve best accuracies as compared to previous models in the literature for optical character recognition (OCR).
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Khan, Lal, Ammar Amjad, Kanwar Muhammad Afaq, and Hsien-Tsung Chang. "Deep Sentiment Analysis Using CNN-LSTM Architecture of English and Roman Urdu Text Shared in Social Media." Applied Sciences 12, no. 5 (March 4, 2022): 2694. http://dx.doi.org/10.3390/app12052694.
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Sentiment analysis (SA) has been an active research subject in the domain of natural language processing due to its important functions in interpreting people’s perspectives and drawing successful opinion-based judgments. On social media, Roman Urdu is one of the most extensively utilized dialects. Sentiment analysis of Roman Urdu is difficult due to its morphological complexities and varied dialects. The purpose of this paper is to evaluate the performance of various word embeddings for Roman Urdu and English dialects using the CNN-LSTM architecture with traditional machine learning classifiers. We introduce a novel deep learning architecture for Roman Urdu and English dialect SA based on two layers: LSTM for long-term dependency preservation and a one-layer CNN model for local feature extraction. To obtain the final classification, the feature maps learned by CNN and LSTM are fed to several machine learning classifiers. Various word embedding models support this concept. Extensive tests on four corpora show that the proposed model performs exceptionally well in Roman Urdu and English text sentiment classification, with an accuracy of 0.904, 0.841, 0.740, and 0.748 against MDPI, RUSA, RUSA-19, and UCL datasets, respectively. The results show that the SVM classifier and the Word2Vec CBOW (Continuous Bag of Words) model are more beneficial options for Roman Urdu sentiment analysis, but that BERT word embedding, two-layer LSTM, and SVM as a classifier function are more suitable options for English language sentiment analysis. The suggested model outperforms existing well-known advanced models on relevant corpora, improving the accuracy by up to 5%.
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Li, Dun, Kanwal Ahmed, Zhiyun Zheng, Syed Agha Hassnain Mohsan, Mohammed H. Alsharif, Hadjouni Myriam, Mona M. Jamjoom, and Samih M. Mostafa. "Roman Urdu Sentiment Analysis Using Transfer Learning." Applied Sciences 12, no. 20 (October 14, 2022): 10344. http://dx.doi.org/10.3390/app122010344.
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Numerous studies have been conducted to meet the growing need for analytic tools capable of processing increasing amounts of textual data available online, and sentiment analysis has emerged as a frontrunner in this field. Current studies are focused on the English language, while minority languages, such as Roman Urdu, are ignored because of their complex syntax and lexical varieties. In recent years, deep neural networks have become the standard in this field. The entire potential of DL models for text SA has not yet been fully explored, despite their early success. For sentiment analysis, CNN has surpassed in accuracy, although it still has some imperfections. To begin, CNNs need a significant amount of data to train. Second, it presumes that all words have the same impact on the polarity of a statement. To fill these voids, this study proposes a CNN with an attention mechanism and transfer learning to improve SA performance. Compared to state-of-the-art methods, our proposed model appears to have achieved greater classification accuracy in experiments.
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Amir, Tehzeeb Sakina, and Anila Amber Malik. "Translation & Validation of Deception as Conflict Management Technique Scale in Urdu." Volume 15 Issue 1, Volume 15 Issue 1 (June 30, 2022): 1–16. http://dx.doi.org/10.34091/ajss.15.1.01.
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The study endeavors Urdu translation and validation of Deception as a Conflict Management Technique Scale (DCMTS). A total of 545 respondents were engaged for the two phased study through convenience sampling. Phase 1 involved forward and backward translation of DCMTS, Phase 2 established its psychometric properties. The reliability & validity of the scale was established using test-retest method & between language validity (English and Urdu versions) of DCMTS, in addition to convergent & discriminant validity with selected sub-scales of Personality Assessment Questionnaire (Urdu adult version). EFA shown factor structure with five principal dimensions; besides confirmatory factor analysis, GFI confirmed good fit of model to data with good values appearing for internal consistency. The findings authenticate that DCMTS is an easy-to-use tool & can be used by counselors and HR professionals to determine the possibility of use of deception. The DCMTS Urdu version will be helpful in clear understanding of the construct regarding the items for Urdu populaces. Keywords: Deception, Urdu translation, reliability and validity, factor analysis
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Ashraf, Zuhab Bin, Shoaib Waqas, Rida Khawar Dar, Muhammad Tariq, Muhammad Nouman Tabassum, and Qurat Ul Ain Sherazi. "Translation and Validation of Childhood Healthcare Assessment Questionnaire in Urdu Language for Juvenile Idiopathic Arthritis." Pakistan Journal of Medical and Health Sciences 17, no. 8 (August 30, 2023): 5–7. http://dx.doi.org/10.53350/pjmhs20231785.
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Aim: To translate and validate Childhood Healthcare Assessment Questionnaire (CHAQ) in Urdu language and assess its psychometric properties for cross cultural adaptation. Methods: The Childhood Healthcare Assessment Questionnaire (CHAQ) was translated into the target language of Urdu by two independent translators, one of whom was familiar with the questionnaire's concept while the other was not, and the two translations were then compared as part of a cross-cultural linguistic validation study. These two initial translations of the questionnaire were blindly reversed, and the results were compared1. The pre-final version of the translated version underwent thorough psychometric testing in a sample of 38 members of the target population (parents of children with juvenile idiopathic arthritis at Ghurki Trust and Teaching Hospital, Lahore) who satisfied the inclusion requirements. The final version was reviewed by an expert panel. Parents' prior approval was obtained before testing. Results: The Cronbach’s alpha for the Urdu version of CHAQ was calculated as 0.993 after testing on the population showing excellent internal consistency. For test-retest reliability, Pearson correlation ranged from (0.378–0.956).The inter-item correlation of the Urdu version of CHAQ after applying to the targeted population has a mean value of 1.177, a minimum value of 0.056, a maximum value of 4.00, a variance value of 0.723, and a range of 3.944. The scale statistics have a mean value of 103.55, a variance of 1462.37, a standard deviation of 38.241, and a total number of items of 88.The intraclass correlation coefficient ranges from 0.606-0.993. Conclusion: The Childhood Healthcare Assessment Questionnaire in Urdu is a screening tool for parents of children with juvenile idiopathic arthritis since it has adequate inter-item correlation values and great internal consistency. Keywords: Childhood Healthcare Assessment Questionnaire (CHAQ), Juvenile Idiopathic Arthritis (JIA), Reliability, Validity, Cross-cultural adaptation
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Mansoor, Sabiha. "Language Planning in Higher Education Issues of Access and Equity." LAHORE JOURNAL OF ECONOMICS 8, no. 2 (July 1, 2003): 17–42. http://dx.doi.org/10.35536/lje.2003.v8.i2.a2.
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Pakistan as a multilingual country faces numerous problems in language planning in higher education. As educational standards in higher education decline, there are concerns about student difficulties in English and lack of required materials in Urdu, The research reported here is a nation wide survey of 2136 students, 121 Subject and English teachers of public and private sector colleges and universities from all the capital cities of Pakistan, as well as 63 parents who responded to the questionnaire. The survey examines the learner's background, attitudes to languages and motivational orientation, availability and quality of materials in different mediums, learner difficulties in English, provision of English support programmes, and language outcomes. Results point to the significant differences between private sector and public sector students in terms of socio-economic status, and other variables. The study recommends that public sector students be provided more state support by adopting an 'English for all policy', and strengthening the English programmes through a revision of courses, development of materials, and training of teachers so as to meet the students' learning and target needs.
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Kottacheruvu, Nagendra. "English Vocabulary Enhancement Strategies for ESL Learners: A Study." International Journal of Language and Literary Studies 5, no. 2 (July 15, 2023): 37–60. http://dx.doi.org/10.36892/ijlls.v5i2.1257.
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Students often spend hours studying through textbooks, practising grammatical exercises, and maybe even viewing the occasional streaming series in the target language in order to acquire proficiency in it. Many individuals, however, are unaware that working on vocabulary is just as crucial, if not more so, than working on grammar when it comes to learning a target language. However, those who do understand the need to learn vocabulary often come across numerous challenges in learning it. The main aim of this study was to investigate effective ways of learning and enhancing vocabulary through surveys and interviews with postgraduate students at Maulana Azad National Urdu University (MANUU).
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Qureshi, Muhammad Aasim, Muhammad Asif, Mohd Fadzil Hassan, Adnan Abid, Asad Kamal, Sohail Safdar, and Rehan Akber. "Sentiment Analysis of Reviews in Natural Language: Roman Urdu as a Case Study." IEEE Access 10 (2022): 24945–54. http://dx.doi.org/10.1109/access.2022.3150172.
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Javed Iqbal, Muhammad, Umme Sadia, and Hafiz Muhammad Qasim. "A Corpus-Based Mechanism of Developing English-Urdu Legal Glossary." Journal of English Language, Literature and Education 5, no. 4 (November 28, 2023): 1–23. http://dx.doi.org/10.54692/jelle.2023.0504192.
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The most creative and educational reference materials for professionals in a specific area, both within and across cultures, are dictionaries. The complete process of creating a bilingual English-Urdu vocabulary of law is addressed in this paper. This includes all phases of the compilation process including planning, terms extraction, parallel corpus construction, and review. It also demonstrates many difficulties the glossary’s writers had while dealing with a large quantity of material and offers sensible solutions for creating a useful output for the audience. The research suggests focusing the efforts on the field of lexicography largely on creating bilingual dictionaries that are both general and specialized, employing an appropriate approach that effectively addresses the demands of the target audience. The study is restricted to addressing the creation of the English-Urdu legal lexicon. On lexicographical conventions with other language pairings, more study be done. Additionally, comparative studies can be carried out to explore their function as valuable resources for various professions across cultural boundaries.
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Thompson, Amy S., and Sandra L. Schneider. "Bridging the Gap." IALLT Journal of Language Learning Technologies 42, no. 1 (April 15, 2012): 1–29. http://dx.doi.org/10.17161/iallt.v42i1.8500.
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As language requirements burgeon at the post-secondary level inattempts to create global citizens out of college graduates,universities nationwide have seen a sharp increase in languagecourse enrollments, especially in the Less Commonly TaughtLanguage (LCTL) courses (Furman, Goldberg, & Lusin, 2007).While this is a positive trend from an intellectual and culturalpoint-of-view, the sudden growth presents a unique set of problemsfor course implementation. There has been a current trend ofoffering language courses online to meet increasing demands forcommonly taught languages (CTLs) (e.g., Chenoweth, Ushida, &Murday, 2006; Sanders, 2005), but little has been written aboutonline offerings for LCTLs (c.f., Winke, Goertler, & Amuzie, 2010).To respond to the need for high-quality pedagogical materials forLCTLs and to compensate for the lack of face-to-face classroomsettings, the Center for the Study of International Languages andCultures (CSILC) at the University of South Florida (USF) hascreated lessons in Dari, Pashto, and Urdu for the Global LanguageOnline Support System website (GLOSS; gloss.dliflc.gov)supported by the Defense Language Institute Foreign LanguageCenter. This paper is an analysis of considerations that informedthe process and products of these modules. A discussion ofimplications and directions for further study concludes the paper.
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SELIHEY, P. O. "INTERNATIONAL AND GLOBAL LANGUAGES: CRITERIA, RATINGS, FORECASTS." Movoznavstvo 320, no. 5 (October 28, 2021): 17–33. http://dx.doi.org/10.33190/0027-2833-320-2021-5-002.
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The article examines the criteria on the basis of which ratings of international languages are compiled and their future is predicted. Language’s chances of becoming international are not highly dependent on its demographic power, structural advantages or ease of learning. What matters most is the influence that speakers of the language have on other peoples. The criteria of «internationality» of the language actually coincide with the criteria of its influence, communicative value, social prestige, sociolinguistic weight. The ratings of the influence of national languages are based on various criteria: state status, communicative potential, economic power, the number of people studying it as a foreign language. These ratings reveal more essential criteria of an international language: prevalence on several continents, the status of an official language in international organizations, value as a source of modern knowledge, a large number of its speakers as a second. A specific feature that brings the international language to the class of world languages should be recognized as its worldwide prevalence. This language is used all over the world, it is spoken (as the first or second) by the majority of the world’s population, its world status is recognized in all countries. The composition of the club of leading languages is constantly changing: some languages come to it, others decrease — depending on the military-political, demographic, economic and cultural success of their speakers. Although the number of speakers of English as a second language is growing steadily, its dominance should be considered as temporary. A new hierarchy of languages may emerge in the middle of 21st century, with other major languages — Chinese, Spanish, Arabic, Hindi/Urdu, competing equally with English in their respective regions. Although state status of the Ukrainian language creates favorable preconditions for its development, it could spread much faster due to its informational value, intellectual power, cultural attractiveness and economic success of Ukraine.
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Nazar, Ramsha, Muhammad Asif Shahzad, and Sidra Saghir. "English Language Learners (ELLs) in Urdu Main Stream: Resources for State-Run Secondary Schools in Punjab Province." Global Language Review VIII, no. II (June 30, 2023): 194–202. http://dx.doi.org/10.31703/glr.2023(viii-ii).17.
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This research analyzed the materials used to teach English in Punjab province's public secondary schools (Pakistan). The objectives of the study were; 1) to find out the availability of resources in English teaching and 2) to explore the utilization of availing resources in the teaching of English. A descriptive research methodology was used for this study. The study's population consisted of all secondary school teachers responsible for instructing their students in English. A total of 400 secondary school instructors were chosen randomly for the study. The study relied on a questionnaire with 21 questions. In pilot testing, the questionnaire had an overall reliability of 0.83. Based on the findings, few modern resources are useful for English teachers in the classroom. Whiteboards, blackboards, charts, and other visual aids are commonly used in classrooms to teach English. English language teachers in Pakistan's Punjab province need more English language teaching (ELT) materials in their classrooms.
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KUMAR, AISHWARJ. "A Marginalized Voice in the History of ‘Hindi’." Modern Asian Studies 47, no. 5 (March 14, 2013): 1706–46. http://dx.doi.org/10.1017/s0026749x12000492.
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AbstractThis paper examines the history of ‘Hindi’1 as a modern Indian language in Bihar between 1850 and 1900. It looks beyond the North-Western Provinces, hitherto the focus of most studies of Hindi, and issues that were important here but not in Bihar like, for example, the ‘Hindi’-Urdu conflict. Instead, it looks at how the ways in which the history of ‘Hindi’ unfolded in Bihar and was distinct from that in other parts of North India. It demonstrates how the regional languages of Bihar were more crucial to the development of ‘Hindi’ in this region than standardized ‘Hindi’, at least until the early twentieth century. A prime focus in this paper is Sir George Abraham Grierson who postulated the theory of an independent ‘Bihari’ language and collected materials to support it. These materials reflect the continuing popularity of Bihari cultural traditions throughout the nineteenth century despite the avowed support for a standardized ‘Hindi’ by the colonial government and the intelligentsia of Bihar. They add a dimension to the historical development of ‘Hindi’ that was distinctive to Bihar. Focussing on this, this paper stresses the part played in the history of ‘Hindi’ by an agent whose voice was marginalized and later ignored or suppressed in canonical accounts of its development as a modern Indian language.
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Chandio, Bilal Ahmed, Ali Shariq Imran, Maheen Bakhtyar, Sher Muhammad Daudpota, and Junaid Baber. "Attention-Based RU-BiLSTM Sentiment Analysis Model for Roman Urdu." Applied Sciences 12, no. 7 (April 4, 2022): 3641. http://dx.doi.org/10.3390/app12073641.
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Deep neural networks have emerged as a leading approach towards handling many natural language processing (NLP) tasks. Deep networks initially conquered the problems of computer vision. However, dealing with sequential data such as text and sound was a nightmare for such networks as traditional deep networks are not reliable in preserving contextual information. This may not harm the results in the case of image processing where we do not care about the sequence, but when we consider the data collected from text for processing, such networks may trigger disastrous results. Moreover, establishing sentence semantics in a colloquial text such as Roman Urdu is a challenge. Additionally, the sparsity and high dimensionality of data in such informal text have encountered a significant challenge for building sentence semantics. To overcome this problem, we propose a deep recurrent architecture RU-BiLSTM based on bidirectional LSTM (BiLSTM) coupled with word embedding and an attention mechanism for sentiment analysis of Roman Urdu. Our proposed model uses the bidirectional LSTM to preserve the context in both directions and the attention mechanism to concentrate on more important features. Eventually, the last dense softmax output layer is used to acquire the binary and ternary classification results. We empirically evaluated our model on two available datasets of Roman Urdu, i.e., RUECD and RUSA-19. Our proposed model outperformed the baseline models on many grounds, and a significant improvement of 6% to 8% is achieved over baseline models.
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Habib, Osama, Azhar Ali Khan, Maryam Javed, Sameer Sattar, Sehrish Sarwar, and Ayesha Jamil. "A Comparison of Psychiatric Rating Scales for the Assessment of Anxiety and Depression in ESRD Patients." Pakistan Journal of Medical and Health Sciences 16, no. 7 (August 31, 2022): 189–91. http://dx.doi.org/10.53350/pjmhs22168189.
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Background: Depression and anxiety are among the most comorbid disorders in End stage renal disease (ESRD) patients. Most of the scales currently in use for screening of anxiety and depression are translated into Urdu language from English. Aga khan university anxiety and depression scales (AKUADS) ,a scale developed in Urdu language contains items that assess for psychological as well as somatic symptoms of anxiety and depression. The aim of the current study was to compare the AKUADS with two other commonly used scales for the detection of anxiety and depression in ESRD patients Materials and methods: Current inpatients at Nephrology unit, Sheikh Zayed Hospital, Lahore who were on dialysis were invited to take part in the study. Patients who provided informed written consent were administered three psychiatric rating scales: AKUADS, patient health questionnaire 9 (PHQ-9) for assessment of depression and General anxiety disorder 7 (GAD-7) for assessment of anxiety. Results: AKUADS was strongly related to both GAD-7 and PHQ-9. The prevalence rate of depression in our patients was 36.4% (Mild depression) as assessed by PHQ-9 and of anxiety was 24.6% as assessed by GAD-7. The prevalence of anxiety and depression as assessed by AKUADS was 33%. Female participants were significantly more likely to have higher scores on all the three scales as compared to male patients Conclusions: AKUADS can be used for the screening of anxiety and depressive disorders in the local population and is well correlated with other more widely used and well validated psychiatric rating scales.
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Ehsan, Toqeer, and Sarmad Hussain. "Analysis of Experiments on Statistical and Neural Parsing for a Morphologically Rich and Free Word Order Language Urdu." IEEE Access 7 (2019): 161776–93. http://dx.doi.org/10.1109/access.2019.2949950.
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Bibi, Saba Mohamed, Cristina Vaqué-Crusellas, and Núria Alonso Pedrol. "Design of Culturally and Linguistically Tailored Nutrition Education Materials to Promote Healthy Eating Habits among Pakistani Women Participating in the PakCat Program in Catalonia." Nutrients 14, no. 24 (December 8, 2022): 5239. http://dx.doi.org/10.3390/nu14245239.
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(1) Background: Pakistani women are among one of Catalonia’s most affected groups by obesity and cardiovascular disease. The design of health education strategies for them has become a compelling need. This paper aims to enlighten the elaboration and evaluation procedure of culturally and linguistically tailored nutrition education materials for Pakistani women participating in the PakCat Program, which aims to evaluate the efficacy of a nutrition education strategy allowing the participants to become ambassadors of healthy eating habits for their community. (2) Methods: In this Randomised Control Trial (RCT), 137 Pakistani women (70 from the intervention and 67 from the control group) took part. We conducted 10 sessions for the intervention group and 3 sessions for the control group in the form of small groups. The sessions were conducted in Urdu and Punjabi, and the material was translated into Urdu, Catalan, Spanish and English. For some sessions, we elaborated on new materials and for others, we adapted them from the existing nutrition material in aspects of language and culture. We evaluated the nutritional material from the observation carried out by the dietician who developed the sessions, participants’ feedback at the end of the sessions and a satisfaction questionnaire. (3) Results: We summarised the elaborated material in form of two multilingual nutritional guidelines about portion size and heart-healthy foods. We also registered several materials generated for the PakCat program such as an infographic about myths and beliefs related to food, a booklet to read and interpret the food labels, a recipe book for healthy snacks, and an infographic of 10 tips for healthy eating. We also organised a PhotoVoice exhibition of 70 healthy plates elaborated by the intervention group participants. The participants highly appreciated the material in terms of visualization, cultural and linguistic adequacy, and level of comprehension through all three evaluation methods. (4) Conclusions: The design of culturally and linguistically tailored nutrition education material for Pakistani women living in Catalonia is attainable and effective to meet their specific needs. The healthy dietary recommendation can be adapted to them preserving their traditional dietary pattern, and they acquire the confidence to start following a healthy diet.
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Khan, Sulaiman, and Shah Nazir. "Deep Learning Based Pashto Characters Recognition." Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences 58, no. 3 (February 3, 2022): 49–58. http://dx.doi.org/10.53560/ppasa(58-3)743.
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In artificial intelligence, text identification and analysis that are based on images play a vital role in the text retrieving process. Automatic text recognition system development is a difficult task in machine learning, but in the case of cursive languages, it poses a big challenge to the research community due to slight changes in character’s shapes and the unavailability of a standard dataset. While this recognition task becomes more challenging in the case of Pashto language due to a large number of characters in its dataset than other similar cursive languages (Persian, Urdu, Arabic) and a slight change in character’s shape. This paper aims to address accept these challenges by developing an optimal optical character recognition (OCR) system to recognise isolated handwritten Pashto characters. The proposed OCR system is developed using multiple long short-term memory (LSTM) based deep learning model. The applicability of the proposed model is validated by using the decision trees (DT) classification tool based on the zoning feature extraction technique and the invariant moment approaches. An overall accuracy rate of 89.03% is calculated for the multiple LSTM-based OCR system while DT-based recognition rate of 72.9% is achieved using zoning feature vector and 74.56% is achieved for invariant moments-based feature map. Applicability of the system is evaluated using different performance metrics of accuracy, f-score, specificity, and varying training and test sets.
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Rehman, Atiq ur, Komal Naveed, Hammad Hassan, Muhammad Aamir Rafique, Anoosha Waseem, and Abdullah Ehsan. "Denture Hygiene Awareness, Practices and Instructional Guidance among Patients in Punjab, Pakistan: a Cross-Sectional Survey." BioMedica 40, no. 1 (March 15, 2024): 37–42. http://dx.doi.org/10.24911/biomedica/5-1018.
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<p><strong>Background and Objective:</strong> Dentures require regular cleaning and without proper guidance on how to clean and care for their dentures, patients may experience discomfort, bad breath, and an increased risk of oral diseases. This study explored the level of awareness, hygiene practices, and the guidance received regarding denture care among individuals wearing dentures in Punjab.<br /><strong>Methods: </strong>This survey was conducted with the agreement of the IRB, using systematic sampling, from November 2021 to August 2022 using a questionnaire developed by the authors, validated through expert review, and administered through interviews. The questions were asked in English language and in Urdu with those who did not understand English language. The survey instrument had 18 items targeting demographics, denture hygiene awareness and practices amongst private and public dental hospital patients. <br /><strong>Results: </strong>There was a statistically significant difference between private and public dental hospitals regarding instructions given for denture hygiene awareness. Most respondents received instructions verbally (83.3%), followed by practical demonstration (20%) and written instructions (9.3%). The majority agreed that unclean dentures have an association with oral (56%) and systemic (70.7%) health and may act as a source of infection (57.3%). A total of 56% of the respondents cleaned their dentures once daily while 16.7% reported halitosis. A significant proportion of the patients had the habit of wearing dentures overnight. <br /><strong>Conclusion: </strong>Approximately half of the patients were aware of the optimal denture hygiene and the implications of wearing unclean dentures. The majority received instructions from dentists verbally and were wearing dentures overnight.</p>
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Zaid, Muhammad, Muhammad Saeed Siddiqui, Hannan Ayub, and Sana Javed. "Preoperative Survey of Patient’s, Understanding of Anaesthesia and the Role of Anaesthesiologists, Undergoing Elective Surgery, at an Urban Tertiary Care Hospital." Pakistan Journal of Medical and Health Sciences 16, no. 8 (August 30, 2022): 342–44. http://dx.doi.org/10.53350/pjmhs22168342.
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Objective: To determine the frequency of patients having adequate knowledge regarding anaesthesia and the role of anaesthesiologists. Study Design: Cross-sectional study. Place and Duration of Study: Department of Anaesthesiology & Critical Care, The Indus Hospital Karachi, Pakistan from 1stJanuary 2017 to 31stMarch 2018. Methodology: Patients presented to the preoperative anaesthesia clinic and or admitted in the hospital for elective surgeries. A pre-coded performa in national language (Urdu) was used for the evaluation of information regarding anaesthesia. Results: 95.1% had correct knowledge about general anaesthesia, 40.6% about local anaesthesia and 43.6% about regional anaesthesia. 71.8% replied that surgeon will determine whether patient is fit for surgery or not. 53% of the patients responded that surgeon will be responsible for the wellbeing of patients during surgery as compare to 36.1% according to whom anaesthetist is responsible for this. Conclusion: Poor understanding of anaesthesiologist’s role both inside and outside the operating room. Educational efforts should be continued, with the goal of alleviating general public’s knowledge regarding this life saving specialty. Keywords: Anaesthesia, Anaesthesiologist, Adequate knowledge
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Ejaz, Lalarukh, Amber Gul Rashid, and Khadija Bari. "The Express Tribune: touching the tricky price point." Emerald Emerging Markets Case Studies 5, no. 3 (June 22, 2015): 1–6. http://dx.doi.org/10.1108/eemcs-04-2014-0087.
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Subject area Economics, entrepreneurship, pricing and marketing strategy, print industry in Pakistan. Study level/applicability Undergraduate and first-year graduate level. Case overview The main theme of the case revolves around decision-making by the publisher, Bilal Lakhani, as he operates in conditions of an oligopolistic market. The case focuses on the set-up of a major English-language newspaper, The Express Tribune, in conjunction with the internationally branded and well-regarded International Herald Tribune by a well-known business group of Pakistan. The group already has a major Urdu newspaper, which has been operational for 15 years, and three television channels, as well as a host of other non-media-related businesses. The case tries to go behind the reasons for setting up an English-language newspaper in a market which already has at least five major existing ones and where literacy is not that widespread. Also, experience in much of the rest of the world would suggest that newspapers – i.e. the print media – are in decline, especially because of the rise of the Internet and social media as means for providing news, information and entertainment. The case is set in Karachi, Pakistan's media capital and, in particular, in an organization that has been involved in the business of media for several years. It currently runs the country's second most-circulated Urdu newspaper, Daily Express. Specifically, the time period is three weeks after the paper, The Express Tribune, was launched into a market with a few competitors and high brand loyalty for existing competitors. The publisher of the paper, Bilal Lakhani, is questioning his pricing decision right after the launch of the paper and there are a series of reasons he is looking into on how he set the original price and why should he reduce the price of the paper now. Expected learning outcomes Students should be able to see, understand and analyze: challenges faced by entrepreneurs of starting an initiative which has a largely unreliable and untested audience; the extent of interdependence in an oligopolistic industry and how it influences the current and future decision-makings of an entrepreneur or any other firm for that matter, especially in a developing economy; the personnel, financial production and regulation issues involved in setting up assembly/ delivery systems that deliver a product for mass use, i.e. a newspaper; and the pricing and marketing strategies involved in the launch and subsequent successful operation of a product, in this case, a newspaper. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.
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Habib, Osama, Fahmina Ashaq, Nauman Ismat Butt, Khalid Mahmood, Azhar Ali Khan, and Mohammad Atif Qureshi. "Does Having a Chronic Liver Illness Make One More Likely to Become Melancholic and Anxious?" Pakistan Journal of Medical and Health Sciences 16, no. 7 (July 30, 2022): 227–29. http://dx.doi.org/10.53350/pjmhs22167227.
Full textAbstract:
Background: Chronic liver disease is a highly prevalent illness globally and in Pakistan as well. The current study was designed to investigate the prevalence of anxiety and depression in patients with chronic liver disease (CLD) in hospitalized patients. Methods and materials: Agha khan University anxiety and depression scale (AKUADS), a questionnaire developed natively in Urdu language, was the instrument used for the study. Admitted patients with the diagnosis of chronic liver disease at a tertiary care hospital in Lahore were invited to take part in the study. A total of 107 patients volunteered to take part in the study (29.9% females) from February 2018 to November 2018. Descriptive statistics was employed to report the prevalence of anxiety and depressive disorders in the study population and independent samples T-test was used to analyze the gender difference between the participants. Results: All study participants scored above the cut-off score of 20 on AKUADS. No significant gender difference was seen among the study participants on mean AKUADS scores. Conclusions: The prevalence of depressive and anxiety disorders is very high in patients with CLD. These patients should be assessed for the presence of depressive and anxiety symptoms on a frequent and routine basis. Recognition and treatment of depressive and anxiety symptoms at an early stage may lead to avoidance of many adverse outcomes related to CLD. Keywords: Depression, Anxiety, Chronic liver disease
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Ferooz, Faria, Malik Tahir Hassan, Sajid Mahmood, Hira Asim, Muhammad Idrees, Muhammad Assam, Abdullah Mohamed, and El-Awady Attia. "Risk and Pattern Analysis of Pakistani Crime Data Using Unsupervised Learning Techniques." Applied Sciences 12, no. 7 (April 6, 2022): 3675. http://dx.doi.org/10.3390/app12073675.
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To reduce crime rates, there is a need to understand and analyse emerging patterns of criminal activities. This study examines the occurrence patterns of crimes using the crime dataset of Lahore, a metropolitan city in Pakistan. The main aim is to facilitate crime investigation and future risk analysis using visualization and unsupervised data mining techniques including clustering and association rule mining. The visualization of data helps to uncover trends present in the crime dataset. The K-modes clustering algorithm is used to perform the exploratory analysis and risk identification of similar criminal activities that can happen in a particular location. The Apriori algorithm is applied to mine frequent patterns of criminal activities that can happen on a particular day, time, and location in the future. The data were acquired from paper-based records of three police stationsin the Urdu language. The data were then translated into English and digitized for automatic analysis. The result helped identify similar crime-related activities that can happen in a particular location, the risk of potential criminal activities occurring on a specific day, time, and place in the future, and frequent crime patterns of different crime types. The proposed work can help the police department to detect crime events and situations and reduce crime incidents in the early stages by providing insights into criminal activity patterns.
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Jadav, Mahesh, and Mohanbhai J. Chavda. "Social reality depicted in Marathi 'Uchalya' autobiography." RESEARCH REVIEW International Journal of Multidisciplinary 8, no. 4 (April 14, 2023): 66–73. http://dx.doi.org/10.31305/rrijm.2023.v08.n04.008.
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Shri Lakshman Gaekwad is the author of autobiography written in original Marathi language called 'Uchalya'. The illustration on the front page of the original Marathi 'Uchalya' work suggests a man standing upside down with his hands tied behind his back, outside a slum of a poor population far from the village. That is, there is a picture of a poor naked man standing helplessly in the bonds of criminality. He is an illiterate, helpless, coercive, criminal prisoner, kept in a kennel away from caste discrimination. Which describes the social condition of our country. This autobiography has been translated into Hindi, English, Kannada, Telugu, Urdu, French, Bengali, Gujarati etc. It has been beautifully translated in Gujarati language by Shri Rabindra Parekh as 'Uthaugir'. This work has received awards like Delhi Sahitya Akademi, Maharashtra Government's Gaurav Award of one lakh rupees, etc. This is his achievement. He is an illiterate, helpless, coercive, criminal prisoner, kept in a kennel away from caste discrimination. Which describes the social condition of our country.
Abstract in Gujarati Lanaguage:
‘ઉચલ્યા’ નામે મૂળ મરાઠીભાષામાં લખાયેલી આત્મકથાના લેખક શ્રી લક્ષ્મણ ગાયકવાડ છે. મૂળ મરાઠી ‘ઉચલ્યા’ કૃતિના મુખપૃષ્ઠ પરનું ચિત્ર સૂચિત અર્થ કરે છે કે, ગામથી દૂર ગરીબ વસ્તીના ઝૂંપડાં બહાર ઉઘાડા શરીરે ઊંધા ઉભેલ પુરુષના હાથ તેની પીઠ પાછળ બંધાયેલા છે. એટલે કે ગુનેગારીના બંધનોમાં બંધાઈને લાચારીવશ નીચો ચહેરો કરી ઊભેલા ગરીબ ઉઘાડડિલ પુરુષનું ચિત્ર છે. તે જાતિગત ભેદભાવથી દૂર હોંશિયામાં રખાયેલ અભણ, લાચારી, મજબૂરીવશ, વિવશતાને લીધે ગુનેગાર થયેલ કેદી છે. જે આપણા દેશની સામાજિક સ્થિતિનું બયાન કરે છે. આ આત્મકથાના હિન્દી, અંગ્રેજી, કન્નડ, તેલુગુ, ઉર્દૂ, ફ્રેન્ચ, બંગાળી, ગુજરાતી વગેરે ભાષાઓમાં અનુવાદ થયા છે. તેનો ગુજરાતી ભાષામાં શ્રીરવીન્દ્ર પારેખે ‘ઉઠાઉગીર’ નામે સુંદર અનુવાદ કર્યો છે. આ કૃતિને દિલ્હી સાહિત્ય અકાદમી, મહારાષ્ટ્ર સરકારનો એક લાખ રૂપિયાનો ગૌરવ પુરસ્કાર વગેરે જેવા પુરસ્કારો પ્રાપ્ત થયા છે. આ તેની સિદ્ધિ છે. તે જાતિગત ભેદભાવથી દૂર હોંશિયામાં રખાયેલ અભણ, લાચારી, મજબૂરીવશ, વિવશતાને લીધે ગુનેગાર થયેલ કેદી છે. જે આપણા દેશની સામાજિક સ્થિતિનું બયાન કરે છે.
Keywords: ઉચલ્યા, પશુતુલ્ય, ઉઠાઉગીર, સંતામુચ્ચર, જાતપંચાયત
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Anum Zulfiqar, Sunia Gul, Hira Riaz, Naseer Ahmad, Syeda Ayesha Absar Hussain, and Syed Adil Tanvir. "KNOWLEDGE AND AWARENESS OF DENTAL IMPLANTS AMONG PATIENTS PRESENTING AT TERTIARY CARE HOSPITAL, ISLAMABAD." Journal of Khyber College of Dentistry 11, no. 03 (September 30, 2021): 14–20. http://dx.doi.org/10.33279/jkcd.v11i03.127.
Full textAbstract:
Objective:To assess the knowledge and awareness of dental implants among a selected number of patients. Materials and Methods:A descriptive cross-sectional study was carried out in Prosthodontics department at Islamic International Dental Hospital Islamabad, on outdoor basis from May 2020 to Oct 2020.A printed performa in the language Urdu, was handed over to the participants visiting the above-mentioned hospital outdoor, and the results were recorded and interpreted in the SPSS version 22 for Mac IOS. Results: We divided our participants in three age groups; 25-50 years old (60.3%), 51-75 years old (36.3%), and 76-100 years old (3.3%). Out of 300, 63.7% participants knew about dental implants while 36.3% did not know about them. The reasons why patients preferred this option were: 8% participants said due to better retention, 3.6% said due to better aesthetics, 34% said they are as good as their natural teeth. On the other hand, the reason for not choosing dental implants was: 8% said they are expensive, 7.3% said they had feared from dental surgery, 5.3% were unsure about the final results, and 0.6% of the participants had medical conditions. Pearson chi-square test was applied in cross-tabulations and p value < 0.05 was considered statistically significant. Conclusion: Results show that participants who were aware of dental implants as a treatment option are relatively significant as compared to those who have no knowledge or awareness regarding them. Maximum information was gained through dentists and the most common reason for opting for dental implants was the consideration that they are as good as their own natural teeth, while the most common barrier for not choosing this option was the high cost of the implant itself.
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Syed Sohaib Daud Gilani, Yasir Khan Khattak, Talwaat Shah, Salman Rasheed, Tauseef Ijaz, Asad Habib, and Iftikhar Qayum. "PREVALENCE AND PREDICTORS OF SELF-MEDICATION PRACTICE WITH ANTIMICROBIALS IN PATIENTS VISITING PUBLIC SECTOR AT HOSPITAL KHAIRABAD DISTRICT NOWSHERA." Journal of Khyber College of Dentistry 10, no. 02 (June 30, 2020): 51–54. http://dx.doi.org/10.33279/jkcd.v10i02.318.
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Objective: To determine the prevalence and patterns of self-medication with antimicrobial drugs among patients visiting public hospital in District Nowshera Northwestern Pakistan. Materials and Methods: This cross-sectional study was conducted on patients attending Rural Health Center Khairabad District Nowshera from July to December 2019. The including criteria were: Males and females (non-doctors) attending the clinics aged between 18 and 60 years old, literate enough to read and write. Information regarding demographic characteristics, antimicrobial drugs use in past six months prior to the study were collected through self-administered questionnaires. The questionnaires written in Urdu and English language, were pretested and validated on a sample of 100 participants to determine the application time and to clarify possible questions from the study population. If antimicrobial drugs use was confirmed in the previous six months, supplementary information was asked: the name antimicrobial drug, the person who recommended the treatment and the disease treated with antimicrobial drugs. The collected data were registered in a database and analyzed using Spss. Results: Response rate of 99.4 %( 750/746) was observed, out of 746 participants 43.70% were females and 56.30% were males. 39.81% participants had used antimicrobials prior to the survey in which 33.33% were from rural and 66.67% urban areas. Most common users were of middle education level. Oral and dental problems were leading cause of inappropriate antimicrobials use. Self- medication was most common in age group of 38 years to 47 years old. The most abused drug was Amoxicillin clavulanate. Maximal use was by personal judgment. Conclusion: The results of this study confirm that self-medication with antimicrobial drugs is a relatively common practice among populace of north western District Nowshera Pakistan.
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Malik, Tariq, Najma Hanif, Ahsen Tahir, Safeer Abbas, Muhammad Shoaib Hanif, Faiza Tariq, Shuja Ansari, Qammer Hussain Abbasi, and Muhammad Ali Imran. "Crowd Control, Planning, and Prediction Using Sentiment Analysis: An Alert System for City Authorities." Applied Sciences 13, no. 3 (January 26, 2023): 1592. http://dx.doi.org/10.3390/app13031592.
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Modern means of communication, economic crises, and political decisions play imperative roles in reshaping political and administrative systems throughout the world. Twitter, a micro-blogging website, has gained paramount importance in terms of public opinion-sharing. Manual intelligence of law enforcement agencies (i.e., in changing situations) cannot cope in real time. Thus, to address this problem, we built an alert system for government authorities in the province of Punjab, Pakistan. The alert system gathers real-time data from Twitter in English and Roman Urdu about forthcoming gatherings (protests, demonstrations, assemblies, rallies, sit-ins, marches, etc.). To determine public sentiment regarding upcoming anti-government gatherings (protests, demonstrations, assemblies, rallies, sit-ins, marches, etc.), the alert system determines the polarity of tweets. Using keywords, the system provides information for future gatherings by extracting the entities like date, time, and location from Twitter data obtained in real time. Our system was trained and tested with different machine learning (ML) algorithms, such as random forest (RF), decision tree (DT), support vector machine (SVM), multinomial naïve Bayes (MNB), and Gaussian naïve Bayes (GNB), along with two vectorization techniques, i.e., term frequency–inverse document frequency (TFIDF) and count vectorization. Moreover, this paper compares the accuracy results of sentiment analysis (SA) of Twitter data by applying supervised machine learning (ML) algorithms. In our research experiment, we used two data sets, i.e., a small data set of 1000 tweets and a large data set of 4000 tweets. Results showed that RF along with count vectorization performed best for the small data set with an accuracy of 82%; with the large data set, MNB along with count vectorization outperformed all other classifiers with an accuracy of 75%. Additionally, language models, e.g., bigram and trigram, were used to generate the word clouds of positive and negative words to visualize the most frequently used words.