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Journal articles on the topic 'Translation into Hindi'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 August 2024

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1

Manikkannan, Prof D. "HINDI TEXT CATEGORIZATION & TRANSLATION." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (2023): 1–10. http://dx.doi.org/10.55041/ijsrem27535.

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The Hindi Text Translation and Categorization aims to develop a comprehensive system for translating and categorizing Hindi text content. This project addresses the growing need for effective language processing tools in the context of Hindi, one of the most widely spoken languages globally. The project consists of two primary components: translation and categorization. The translation module employs state-of-the-art machine translation techniques to provide accurate and contextually relevant translations between Hindi and other languages. This functionality is essential for breaking down lang

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Madaan, Vishu, and Prateek Agrawal. "Anuvaad." International Journal of Social Ecology and Sustainable Development 13, no. 1 (2022): 1–14. http://dx.doi.org/10.4018/ijsesd.295088.

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Machine Translation is best alternative to traditional manual translation. The corpus of Sanskrit literature includes a rich tradition of philosophical and religious texts as well as poetry, music, drama, scientific, technical and other texts. Due to the modernization of tradition and languages, Sanskrit is not on everyone's lips. Translation makes it convenient for users to understand the unknown text. This paper presents a language Machine Translation System from Hindi to Sanskrit and Sanskrit to Hindi using a rule-based technique. We developed a machine translation tool 'anuvaad' which tran

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Sharma, Sandeep. "Short Note: Chichewa and Hindi Back Translations of the Bible: A Comparative Check of Translation Techniques." Journal of Translation 14, no. 1 (2018): 42–47. http://dx.doi.org/10.54395/jot-69624.

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The Bible in India has been seen by some as an offshoot of the missionary movement in pre- and post-independence times. Such allegations belie a technical or stylistic reading of the translated scriptures into Hindi, which is the great unread aspect of the Bible. The Bible translated into Hindi is titled Dharmasastra. The present study aims to compare the Hindi version with another translation in a completely different part of the world, the Chichewa Bible. Chichewa is a Bantu language widely spoken in SE Africa. It turns out that the Hindi translation of the Bible is surprisingly close to the

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Iyengar, Srinivasan, Shirish Karande, and Sachin Lodha. "English to Hindi Translation Protocols for an Enterprise Crowd." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 1 (November 3, 2013): 34–35. http://dx.doi.org/10.1609/hcomp.v1i1.13125.

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We present early results on crowd sourcing translations in an enterprise setting. We show that several weak translators can together converge to translation quality higher than individually plausible. We share learning about post editing of translations and the effort perceived by the crowd. A key observation is that a protocol “machine-human-human” that utilizes two-hop post editing can provide an almost expert quality translation. Finally, we discuss methods that can choose the best translation among several candidates.

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Mukhopadhyay, Subhodeep. "Lost in Untranslatability: Ishvara, Allah and Interfaith Dialogue." June-July 2024, no. 44 (June 13, 2024): 1–9. http://dx.doi.org/10.55529/jlls.44.1.9.

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While translation plays a vital role in bridging intercultural gaps, it struggles to convey the exact meaning of certain ideas due to the unique characteristics and structures inherent in each language and the underlying social context. This difficulty is pronounced when translating between the language pair Hindi and Urdu, which, despite both originating from Khari Boli, have diverged significantly under the influences of Hinduism and Islam. In an Indian social context, the Arabic-origin Urdu word Allah is often equated with the Sanskrit-origin Hindi word Ishvara. However, this translation is

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Mukhopadhyay, Subhodeep. "Lost in Untranslatability: Ishvara, Allah and Interfaith Dialogue." June-July 2024, no. 44 (June 13, 2024): 1–9. http://dx.doi.org/10.55529/10.55529/jlls.44.1.9.

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While translation plays a vital role in bridging intercultural gaps, it struggles to convey the exact meaning of certain ideas due to the unique characteristics and structures inherent in each language and the underlying social context. This difficulty is pronounced when translating between the language pair Hindi and Urdu, which, despite both originating from Khari Boli, have diverged significantly under the influences of Hinduism and Islam. In an Indian social context, the Arabic-origin Urdu word Allah is often equated with the Sanskrit-origin Hindi word Ishvara. However, this translation is

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Gangwar, Sonali, and Iram Naim. "Development of Offline Translation Software for English to Hindi." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 582–85. http://dx.doi.org/10.22214/ijraset.2024.59808.

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Abstract: This article provides a comprehensive study on the development of offline applications for English to Hindi translation. The project leverages the Moses statistical machine translation system to achieve the goal of seamless text-to-text translation between two languages without the need for online APIs. The report covers many aspects of the project, including methods for learning translation techniques and using dynamic programming to calculate the cheapest possible translation methods for foreign languages. Carefully consider the translation by analyzing the quoted words one after t

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Pandey, Vikas, Dr M. V. Padmavati, and Dr Ramesh Kumar. "Hindi Chhattisgarhi Machine Translation System Using Statistical Approach." Webology 18, Special Issue 02 (2021): 208–22. http://dx.doi.org/10.14704/web/v18si02/web18067.

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Machine Translation is a subfield of Natural language Processing (NLP) which uses to translate source language to target language. In this paper an attempt has been made to make a Hindi Chhattisgarhi machine translation system which is based on statistical approach. In the state of Chhattisgarh there is a long awaited need for Hindi to Chhattisgarhi machine translation system for converting Hindi into Chhattisgarhi especially for non Chhattisgarhi speaking people. In order to develop Hindi Chhattisgarhi statistical machine translation system an open source software called Moses is used. Moses

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Kammar, Prashanth, Parashuram Baraki, Sunil Kumar Ganganayaka, Manjunath Swamy Byranahalli Eraiah, and Kolakaluri Lakshman Arun Kumar. "Sanskrit to Hindi language translation using multimodal neural machine translation." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 2 (2024): 1235. http://dx.doi.org/10.11591/ijeecs.v34.i2.pp1235-1245.

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Machine translation (MT) is a subfield of computer features that focuses on the automatic translation from one natural language into another without any human involvement. Due to native people interacting in a variety of languages, there is a great need for translating information between languages to send and communicate thoughts. However, they disregard the significance of semantic data encoded in the text features. In this paper, multimodal neural machine translation (MNMT) is proposed for Sanskrit-Hindi translation. The main goal of the proposed method is to fully utilize semantic text fea

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Singh, Arvinder, Ninad Bhase, Manav Jain, and Tushar Ghorpade. "Machine Translation Systems for English Captions to Hindi Language Using Deep Learning." ITM Web of Conferences 44 (2022): 03004. http://dx.doi.org/10.1051/itmconf/20224403004.

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Machine Translation is the process of translating text from one language to another which helps to reduce the conversation gap among people from different cultural backgrounds. The task performed by the Machine Translation System is to automatically translate between pairs of different natural languages, where Neural Machine Translation System stands out from all because it provides fluent translation along with reasonable translation accuracy. The Convolution Neural Network encoder is used to find patterns in the images and encode it into a vector that is passed to the Long Short Term Memory

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Jain, Anjali, and T. Megha Sheth. "Ab. No. 60 Translation and Cross-Cultural Adaptation of Health Literacy Instrument for Adults in Hindi." Journal of Society of Indian Physiotherapists 8, no. 1 (2024): 57–58. http://dx.doi.org/10.4103/jsip.jsip_abstract_25.

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Introduction: Physiotherapists play a significant role in health promotion and wellness. Health literacy can help people prevent health problems, protect health and better manage diseases when they arise. To Translate and Cross Culturally Adapt Health Literacy Instrument for Adults (HELIA) and Determine the Reliability and Validity. Methods: Adults aged 18-65 years were included. Methodological study was done where permission to translate the scale was taken from the author. The health literacy instrument for adults was translated into Hindi using forward-backward translation method given by W

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Verma, Aishwarya R. "Comparative Analysis of Language Translation and Detection System Using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (2021): 1200–1211. http://dx.doi.org/10.22214/ijraset.2021.37577.

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Abstract: Words are the meaty component which can be expressed through speech, writing or signals. It is important that the actual message or meaning of the words sent must conveys the same meaning to the one receives. The evolution from manual language translator to the digital machine translation have helped us a lot for finding the exact meaning such that each word must give at least close to exact actual meaning. To make machine translator more human-friendly feeling, natural language processing (NLP) with machine learning (ML) can make the best combination. The main challenges in machine

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Waghmare, Samruddhi. "Hindi to English Translation using NLTK." International Journal for Research in Applied Science and Engineering Technology 7, no. 12 (2019): 227–29. http://dx.doi.org/10.22214/ijraset.2019.12037.

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Goswami, Pankaj K., Sanjay K. Dwivedi, and C. K. Jha. "Assessment of Multi-Engine Machine Translation for English to Hindi Language (MEMTEHiL)." International Journal of Artificial Life Research 6, no. 1 (2016): 30–45. http://dx.doi.org/10.4018/ijalr.2016010102.

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English to Hindi translation of the computer-science related e-content, generated through an online freely available machine translation engine may not be technically correct. The expected target translation should be as fluent as intended for the native learners and the meaning of a source e-content should be conveyed properly. A Multi-Engine Machine Translation for English to Hindi Language (MEMTEHiL) framework has been designed and integrated by the authors as a translation solution for the computer science domain e-content. It was possible by enabling the use of well-tested approaches of m

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Kumar, Pursotam, and Anil Kumar Thakur. "English-to-Hindi Mapping of Compositional Verb-Particle Constructions." International Journal of Religion 5, no. 4 (2024): 171–78. http://dx.doi.org/10.61707/rvfr2948.

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The present study investigates the semantic correspondence in the Hindi translation equivalents of compositional English verb-particle constructions (EVPCs) with the particle up. The compositional constructions include the directional and aspectual functions of particles. The study concentrates on the semantic representation of literal spatial directional and aspectual completive functions of the particle up in Hindi, a major Indian language. The researchers selected some frequent EVPCs, took examples from the British National Corpus and manually translated them into Hindi with the help of rel

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Narayan, Ravi, V. P. Singh, and S. Chakraverty. "Quantum Neural Network Based Machine Translator for Hindi to English." Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/485737.

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This paper presents the machine learning based machine translation system for Hindi to English, which learns the semantically correct corpus. The quantum neural based pattern recognizer is used to recognize and learn the pattern of corpus, using the information of part of speech of individual word in the corpus, like a human. The system performs the machine translation using its knowledge gained during the learning by inputting the pair of sentences of Devnagri-Hindi and English. To analyze the effectiveness of the proposed approach, 2600 sentences have been evaluated during simulation and eva

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Shirsath, Nilesh, Aniruddha Velankar, Ranjeet Patil, and Shilpa Shinde. "Various Approaches of Machine Translation for Marathi to English Language." ITM Web of Conferences 40 (2021): 03026. http://dx.doi.org/10.1051/itmconf/20214003026.

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Machine Translation (MT) is a generic term for computerised systems that generate translations from one natural language to another, with or without human intervention. Text may be used to examine knowledge, and turning that information into pictures helps people to communicate and acquire information.There seems to be a lot of work conducted on translating English to Hindi, Tamil, Bangla and other languages. The important parts of translation are to provide translated sentences with correct words and proper grammar. There has been a comprehensive review of 10 primary publications used in rese

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Malik, Pooja, Y. Mrudula, and Anurag S. Baghel. "Statistical Analysis of Machine Translation Evaluation Systems for English- Hindi Language Pair." Recent Advances in Computer Science and Communications 13, no. 5 (2020): 864–70. http://dx.doi.org/10.2174/2213275912666190716100145.

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Background: Automatic Machine Translation (AMT) Evaluation Metrics have become popular in the Machine Translation Community in recent times. This is because of the popularity of Machine Translation engines and Machine Translation as a field itself. Translator is a very important tool to break barriers between communities especially in countries like India, where people speak 22 different languages and their many variations. With the onset of Machine Translation engines, there is a need for a system that evaluates how well these are performing. This is where machine translation evaluation enter

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Pathak, Amarnath, and Partha Pakray. "Neural Machine Translation for Indian Languages." Journal of Intelligent Systems 28, no. 3 (2019): 465–77. http://dx.doi.org/10.1515/jisys-2018-0065.

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Abstract Machine Translation bridges communication barriers and eases interaction among people having different linguistic backgrounds. Machine Translation mechanisms exploit a range of techniques and linguistic resources for translation prediction. Neural machine translation (NMT), in particular, seeks optimality in translation through training of neural network, using a parallel corpus having a considerable number of instances in the form of a parallel running source and target sentences. Easy availability of parallel corpora for major Indian language forms and the ability of NMT systems to

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Jaya, K., and Deepa Gupta. "Exploration of Corpus Augmentation Approach for English-Hindi Bidirectional Statistical Machine Translation System." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 3 (2016): 1059. http://dx.doi.org/10.11591/ijece.v6i3.8904.

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Even though lot of Statistical Machine Translation(SMT) research work is happening for English-Hindi language pair, there is no effort done to standardize the dataset. Each of the research work uses different dataset, different parameters and different number of sentences during various phases of translation resulting in varied translation output. So comparing these models, understand the result of these models, to get insight into corpus behavior for these models, regenerating the result of these research work becomes tedious. This necessitates the need for standardization of dataset and to i

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Jaya, K., and Deepa Gupta. "Exploration of Corpus Augmentation Approach for English-Hindi Bidirectional Statistical Machine Translation System." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 3 (2016): 1059. http://dx.doi.org/10.11591/ijece.v6i3.pp1059-1071.

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Even though lot of Statistical Machine Translation(SMT) research work is happening for English-Hindi language pair, there is no effort done to standardize the dataset. Each of the research work uses different dataset, different parameters and different number of sentences during various phases of translation resulting in varied translation output. So comparing these models, understand the result of these models, to get insight into corpus behavior for these models, regenerating the result of these research work becomes tedious. This necessitates the need for standardization of dataset and to i

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Premjith, B., M. Anand Kumar, and K. P. Soman. "Neural Machine Translation System for English to Indian Language Translation Using MTIL Parallel Corpus." Journal of Intelligent Systems 28, no. 3 (2019): 387–98. http://dx.doi.org/10.1515/jisys-2019-2510.

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Abstract Introduction of deep neural networks to the machine translation research ameliorated conventional machine translation systems in multiple ways, specifically in terms of translation quality. The ability of deep neural networks to learn a sensible representation of words is one of the major reasons for this improvement. Despite machine translation using deep neural architecture is showing state-of-the-art results in translating European languages, we cannot directly apply these algorithms in Indian languages mainly because of two reasons: unavailability of the good corpus and Indian lan

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Mittal, Aditya. "Neural Machine Translation from English to Hindi." International Journal for Research in Applied Science and Engineering Technology 8, no. 5 (2020): 2943–48. http://dx.doi.org/10.22214/ijraset.2020.5494.

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Gaikwad, Siddheshwar. "English translation of 'Barrister': Dialectics and Balance." RESEARCH HUB International Multidisciplinary Research Journal 9, no. 2 (2022): 10–13. http://dx.doi.org/10.53573/rhimrj.2022.v09i02.002.

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Barrister is a famous Marathi play written by Jaywant Dalvi. Dalvi ji is recognized as a fine writer in the Marathi theater field. Barrister is a dramatization published in 1977. Three years after the original was published, Dr. Vijay Bapat translated it into Hindi in 1980 and placed it in front of the theater-loving readers of the Hindi region. The play deals with social themes, in which the pathetic condition of widows has been clarified. Dr. Vijay Bapat has translated it into Hindi as this topic is new for Hindi theatrical lovers. It is not possible to discuss the entire dramatization here

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Kumari, Rajbala, Jay Kumar Ranjan, and Saroj Verma. "Psychometric Properties of the Hindi Version of the Behavioral Inhibition System/Behavioral Activation System Scale." Psychological Test Adaptation and Development 5, no. 1 (2024): 66–79. http://dx.doi.org/10.1027/2698-1866/a000069.

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Abstract: Aim: The Behavioral Inhibition and Activation Scale is a popular instrument that assesses an individual's responsiveness to reward and punishment. It is widely translated and validated in different languages. However, the Hindi version of this scale is not yet available. The present study aimed to adapt the BIS/BAS scale into Hindi and examine its psychometric properties and factor structure. Method: The original BIS/BAS scale was translated into Hindi using the translation and back-translation method. The translated Hindi version along with the NEO-FFI and HADS was administered on 2

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Dwivedi, Sanjay K., and Pramod P. Sukhadeve. "English to Hindi Paraphrase Convention for Translating Homoeopathy Literature." International Journal of Artificial Life Research 3, no. 4 (2012): 66–74. http://dx.doi.org/10.4018/ijalr.2012100105.

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The rule based approach to machine translation (MT) confines grammatical rules between the source and the target language with the goal of constructing grammatical translation between the language pair. In this paper, we describe the structural representation of English stemmer, POS tagging and design transfer rules which can generate Hindi sentence from the structural representation of the English sentence. Due to the specific terminology of homoeopathic sentences and the linguistic gap between the two languages the translation of these literatures form English to Hindi is a challenging task.

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Rani, Sumita, and Dr Vijay Luxmi. "Direct Machine Translation System from Punjabi to Hindi for Newspapers headlines Domain." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 8, no. 3 (2013): 908–12. http://dx.doi.org/10.24297/ijct.v8i3.3402.

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Machine Translation System is an important area in Natural Language Processing. The Direct MT system is based upon the utilization of syntactic and vocabulary similarities between more or few related natural languages. The relation between two or more languages is based upon their common parent language. The similarity between Punjabi and Hindi languages is due to their parent language Sanskrit. Punjabi and Hindi are closely related languages with lots of similarities in syntax and vocabulary. In the present paper, Direct Machine Translation System from Punjabi to Hindi has been developed and

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Chandra, Ganesh, and Sanjay K. Dwivedi. "Assessing Query Translation Quality Using Back Translation in Hindi-English CLIR." International Journal of Intelligent Systems and Applications 9, no. 3 (2017): 51–59. http://dx.doi.org/10.5815/ijisa.2017.03.07.

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Jain, Jyotsna, Sanjukta Ghosh, Snehil Gupta, and Sai Sreeja Vullanki. "Development of Hindi-Translated Version of the Female Sexual Function Index for Evaluating Sexual Dysfunctions among Individuals with Anxiety, Depression, and Other Common Mental Health Conditions: Experiential Account and Preliminary Findings from India." Psychiatry International 4, no. 2 (2023): 160–73. http://dx.doi.org/10.3390/psychiatryint4020018.

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Sexual dysfunctions are common among females with common mental health conditions, such as anxiety and depression. However, discussion on this topic remains taboo in many cultures, including India. Worldwide, the Female Sexual Function Index (FSFI) is the most used tool to evaluate sexual functioning in females. Researchers across the globe attempted to translate and validate this scale in native languages (e.g., Japanese and Spanish); however, such translations are not available in Hindi. Strikingly, although there is literature informing us about the regional validation process of this scale

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Barman, Anup Kumar, Jumi Sarmah, Subungshri Basimatary, and Amitava Nag. "Word Sense Disambiguation applied to Assamese-Hindi Bilingual Statistical Machine Translation." Engineering, Technology & Applied Science Research 14, no. 1 (2024): 12581–86. http://dx.doi.org/10.48084/etasr.6342.

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Word Sense Disambiguation (WSD) is concerned with automatically assigning the appropriate sense to an ambiguous word. WSD is an important task and plays a crucial role in many Natural Language Processing (NLP) applications. A Statistical Machine Translation (SMT) system translates a source into a target language based on phrase-based statistical translation. MT plays a crucial role in a WSD system, as a source language word may be associated with multiple translations in the target language. This study aims to apply WSD to the input of the MT system to enhance the disambiguation output. Hindi

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Bhadwal, Neha, Prateek Agrawal, and Vishu Madaan. "A Machine Translation System from Hindi to Sanskrit Language using Rule based Approach." Scalable Computing: Practice and Experience 21, no. 3 (2020): 543–54. http://dx.doi.org/10.12694/scpe.v21i3.1783.

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Machine Translation is an area of Natural Language Processing which can replace the laborious task of manual translation. Sanskrit language is among the ancient Indo-Aryan languages. There are numerous works of art and literature in Sanskrit. It has also been a medium for creating treatise of philosophical work as well as works on logic, astronomy and mathematics. On the other hand, Hindi is the most prominent language of India. Moreover,it is among the most widely spoken languages across the world. This paper is an effort to bridge the language barrier between Hindi and Sanskrit language such

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Gupta, Vivek. "Arabic in Hindustan: Comparative Poetics in the Eighteenth Century and Azad Bilgrami’s The Coral Rosary." Journal of South Asian Intellectual History 4, no. 2 (2022): 181–222. http://dx.doi.org/10.1163/25425552-12340034.

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Abstract This article examines the contributions of Ghulām ʿAlī “Āzād” Bilgrāmī (1704–1786) to our understanding of comparative poetics and Arabic in eighteenth-century Hindustan. It attends to Azad’s oeuvre through the lenses of translation, multilingualism, and literary science. Philological analysis reveals how Azad establishes analogues across these three literary languages that attest to the adaptive capacity of poetics. His sections on Hindi poetry in his Arabic work Subḥat al-marjān fī āthār Hindūstān (The Coral Rosary of Hindustan’s Traditions, 1763–64), and its later adaptation into P

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Anuradha, V., Saira Siddiqui, and Mariya Sheema. "Multilingual Composition in Translated Versions of Premchand's Selected Short Stories." International Journal of English Learning & Teaching Skills 4, no. 4 (2022): 1–13. http://dx.doi.org/10.15864/ijelts.4402.

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Throughout history, written and spoken translations have played a crucial role in inter-human communication, providing access to important texts for scholarship and religious purposes. The practice of translating is longestablished, but the discipline of translation studies is new. In academic circles, translation was previously related to just a language-learning activity. The study of literary translation began through comparative literature, translation workshops and contrastive analysis. Translation studies have expanded hugely and are now often considered interdisciplinary. History of Ind

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Verma, Kanchan. "Hindi Adaptation and validation of Body Image Concern Inventory." Mind and Society 12, no. 01 (2023): 33–40. http://dx.doi.org/10.56011/mind-mri-121-20234.

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The present study aimed to adapt Body Image Concern Inventory (BICI) into Hindi language and assess the psychometric properties of the scale in Hindi speaking population. This scale was originally developed by Littleton, Axson and Pure in 2005. World Health Organization guideline of translation and adaptation of scale has been followed to translate this scale into Hindi. After the completion of translation process, the Hindi version of BICI, Body Dissatisfaction Scale, Rosenberg’s Self-esteem Scale, and General Mental Health Questionnaire-28 has been administered to the sample. The age range o

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Kumar K., Vimal, and Divakar Yadav. "Word Sense Based Hindi-Tamil Statistical Machine Translation." International Journal of Intelligent Information Technologies 14, no. 1 (2018): 17–27. http://dx.doi.org/10.4018/ijiit.2018010102.

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Corpus based natural language processing has emerged with great success in recent years. It is not only used for languages like English, French, Spanish, and Hindi but also is widely used for languages like Tamil, Telugu etc. This paper focuses to increase the accuracy of machine translation from Hindi to Tamil by considering the word's sense as well as its part-of-speech. This system works on word by word translation from Hindi to Tamil language which makes use of additional information such as the preceding words, the current word's part of speech and the word's sense itself. For such a tran

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Bąkowski, Jacek. "Translation of Perso-Arabic loanwords from Hindi into Polish: A pilot study." Lodz Papers in Pragmatics 18, no. 2 (2022): 289–302. http://dx.doi.org/10.1515/lpp-2022-0014.

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Abstract In contemporary literary Hindi there is an abundance of Perso-Arabic loanwords which often function similarly to words of Sanskrit origin. Despite their semantic proximity, each of them can have different connotational meanings and cultural associations. Furthermore, depending on the context, one of them will be preferred to the other. This situation can become an issue when translating from Hindi into Polish. In this paper, I will investigate whether these loanwords should be considered as a third language in translation. If this is the case, they make the text a multicultural one, a

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Tripathi, Samiksha, and Vineet Kansal. "Machine Translation Evaluation: Unveiling the Role of Dense Sentence Vector Embedding for Morphologically Rich Language." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 01 (2019): 2059001. http://dx.doi.org/10.1142/s0218001420590016.

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Machine Translation (MT) evaluation metrics like BiLingual Evaluation Understudy (BLEU) and Metric for Evaluation of Translation with Explicit Ordering (METEOR) are known to have poor performance for word-order and morphologically rich languages. Application of linguistic knowledge to evaluate MTs for morphologically rich language like Hindi as a target language, is shown to be more effective and accurate [S. Tripathi and V. Kansal, Using linguistic knowledge for machine translation evaluation with Hindi as a target language, Comput. Sist.21(4) (2017) 717–724]. Leveraging the recent progress m

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Kaur, Jagroop, and Gurpreet Singh Josan. "English to Hindi Multi Modal Image Caption Translation." Journal of scientific research 64, no. 02 (2020): 274–81. http://dx.doi.org/10.37398/jsr.2020.640238.

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Lewis, ChristopherAlan, Sadia Musharraf, and MaryJane Lewis. "Abbreviated form revised eysenck personality questionnaire: Hindi translation." Archives of Mental Health 15, no. 1 (2014): 139. http://dx.doi.org/10.4103/2589-9171.227698.

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Lewis, ChristopherAlan, Sadia Musharraf, and MaryJane Lewis. "Abbreviated form revised eysenck personality questionnaire: Hindi translation." Archives of Mental Health 15, no. 1 (2014): 139. http://dx.doi.org/10.4103/2589-9171.227875.

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Rishikesh, Dr Kumar. "Problems in Translating Fictions." SMART MOVES JOURNAL IJELLH 8, no. 3 (2020): 11. http://dx.doi.org/10.24113/ijellh.v8i3.10459.

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The present paper tries to look into the socio-linguistic challenges and barriers concerned with translation of literary prose as prose constitutes ideologies, cultural values, as well as social, political, psychological and philosophical world views which always remain anthropocentric. Comparison of the original titles of the Hindi stories of Premchand and its translation as well as the interpretative role of the translator have been critically evaluated to establish the fact that a successful translator apart from mapping location, identities and cultural conflicts of the source language and

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Dubey, Namrata, Naoko Witzel, and Jeffrey Witzel. "Script differences and masked translation priming: Evidence from Hindi-English bilinguals." Quarterly Journal of Experimental Psychology 71, no. 11 (2018): 2421–38. http://dx.doi.org/10.1177/1747021817743241.

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This study reports on two experiments investigating the effects of script differences on masked translation priming in highly proficient early Hindi-English bilinguals. In Experiment 1 (the cross-script experiment), L1 Hindi was presented in the standard Devanagari script, while L2 English was presented in the Roman alphabet. In Experiment 2 (the same-script experiment), both L1 Hindi and L2 English were presented in the Roman alphabet. Both experiments revealed translation priming in the L1-L2 direction. However, L2-L1 priming was obtained in the same-script experiment, but not in the cross-s

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Gupta, Ravi, Ramjan Ali, Mohan Dhyani, Sourav Das, and Ashwini Pundir. "Hindi translation of Berlin questionnaire and its validation as a screening instrument for obstructive sleep apnea." Journal of Neurosciences in Rural Practice 07, no. 02 (2016): 244–49. http://dx.doi.org/10.4103/0976-3147.176187.

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ABSTRACT Background: Obstructive sleep apnea (OSA) is a fairly common problem with adverse health consequences. However, any screening questionnaire is not available in Hindi to screen sleep apnea. Materials and Methods: Subjects undergoing video-synchronized in laboratory attended polysomnography were requested to participate in this study. They were screened with the help of Hindi version of Berlin questionnaire (BQ). Outcome of the BQ was tested against the gold standard polysomnography. Descriptive statistics, sensitivity, specificity, positive predictive value (PPV), and negative predicti

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Shi, Xiayang, and Zhenqiang Yu. "Adding Visual Information to Improve Multimodal Machine Translation for Low-Resource Language." Mathematical Problems in Engineering 2022 (August 30, 2022): 1–9. http://dx.doi.org/10.1155/2022/5483535.

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Machine translation makes it easy for people to communicate across languages. Multimodal machine translation is also one of the important directions of research in machine translation, which uses feature information such as images and audio to assist translation models in obtaining higher quality target languages. However, in the vast majority of current research work has been conducted on the basis of commonly used corpora such as English, French, German, less research has been done on low-resource languages, and this has left the translation of low-resource languages relatively behind. This

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Srivastava, Pankaj Bala. "Problems and Prospects of Translating Indian Literature: With Particular Reference to Geetanjali Shree's Ret Samadhi." Dialogue: A Journal Devoted to Literary Appreciation 19, no. 01 (2023): 13–20. http://dx.doi.org/10.30949/dajdtla.v19i1.2.

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    Many of us have read Tolstoy, Dostoevsky, Voltaire, Anne Frank, Marquez, Murakami, Borges or even Valmiki, Kalidas, Tagore, Kabeer and Premchand only in translation. Some things are mislaid in translation, but the gains are enormous. Translations brighten the rich literary world of Indian languages and literature. 'Ret Samadhi' (2018), a Hindi-language novel by Indian author Geetanjali Shree, is deftly translated by Annie Montaut into French as 'au-delà de la frontière' (Beyond the Border, 2020) and Daisy Rockwell into English as 'Tomb of Sand' (2022) for a global

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Gupta, Ekta, and Shailendra Shrivastava. "Analysis on Translation Quality of English to Hindi Online Translation Systems- A Review." International Journal of Computer Applications 152, no. 10 (2016): 42–46. http://dx.doi.org/10.5120/ijca2016911749.

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Gupta, Ekta, and Shailendra Kumar. "A Result Analysis of Translation Techniques of English to Hindi Online Translation Systems." International Journal of Computer Applications 156, no. 12 (2016): 12–15. http://dx.doi.org/10.5120/ijca2016912501.

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Sahu, Prachi, Pragya Chaturvedi, Rahul Khan, Monika Singla, Anjana Munshi, and Gagandeep Singh. "Translation and Validation of ID-Migraine Questionnaire to North-Indian Vernacular Languages." Annals of Indian Academy of Neurology 26, no. 4 (2023): 543–48. http://dx.doi.org/10.4103/aian.aian_223_23.

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Abstract Background: ID-Migraine is an established screening tool for migraine. Translation and validation in more languages can increase its reach and scope. Aim: To translate and validate ID-Migraine for screening migraine patients in two North-Indian vernacular languages, that is, Hindi and Punjabi. Methods: ID Migraine was translated into Hindi and Punjabi. Subjects with headaches in outpatient clinics were administered the questionnaire according to their preferred language of choice and referenced clinical evaluations, performed by an experienced neurologist, based on current the ICHD-3

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Malik, Renuka, Chanderkala Pokaria, Swati Singh, and Kaveri Khera. "Hindi translated version of menopausal rating score questionnaire: a method to evaluate post menopausal symptoms in India." International Journal of Reproduction, Contraception, Obstetrics and Gynecology 8, no. 8 (2019): 3102. http://dx.doi.org/10.18203/2320-1770.ijrcog20193519.

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Background: There are large number of post menopausal patients in India deserving more care and attention than is given at present.MRS questionnaire in Hindi (MRS-H), a translated and validated version of original MRS Scale (MRS-E), self assessed by patients in their own native language. This tool can be used to assess and document current quality of life as well as improvement with treatment of severe post menopausal symptoms, in Indian population.Methods: 30 bilingual English and Hindi speaking postmenopausal patients were recruited for this study.MRS Questionnaire has 11 questions covering

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Chakrawarti, Rajesh Kumar, and Pratosh Bansal. "Approaches for Improving Hindi to English Machine Translation System." Indian Journal of Science and Technology 10, no. 16 (2017): 1–8. http://dx.doi.org/10.17485/ijst/2017/v10i16/111895.

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