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• Word order typology and its implication in translation , with N. Gejeswari, in Language in India (2019)

• A historical linguistic study of Tamil nouns , with S. Tamilselvam, in Language in India (2019)

• Semantic change and semantic extension of Tamil verbs : a research monograph in Tamil , with K. Bakkiyaraj, in Language in India (2019)

• studies about the Tamil language, by Jean-Luc Chevillard

• On Tamil poetical compositions and their "limbs" , as described by Tamil grammarians , in Histoire, épistémologie, langage (2011)

• Les particules énonciatives -ee et -taa n , in Faits de langues (1997)

• Les mots dans la tradition tamoule classique , in Histoire, épistémologie, langage (2002)

• Sur l'adjectif dans la tradition grammaticale tamoule , in Histoire, épistémologie, langage (1992)

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• Le vocabulaire de la deixis dans la tradition grammaticale tamoule , in Histoire, épistémologie, langage (1998)

• Beschi, grammairien du tamoul et l'origine de la notion de verbe appellatif , in Bulletin de l'École française d'Extrême-Orient (1992)

• Sur la classification des noms chez des grammairiens autochtones et occidentaux du tamoul , in Bulletin de l'École française d'Extrême-Orient (1993)

• Remarques sur l'évolution du système des temps en tamoul (1991)

• La personne en tamoul classique  : théories et faits , in Faits de langues (1994)

• Costanzo Giuseppe Beschi (1680-1747): from Jesuit Missionary to Tamil Pulavar , by Margherita Trento & Sascha Ebeling, in L'Inde et l'Italie (2018)

• The linguistic and historical contribution of the Arte Tamulica by Baltasar da Costa (~1610-1673): annotated and commented Portuguese transcription and English translation from Portuguese and Tamil , by Cristina Muru, thesis (2022)

• Mission linguistique  : l'indigénisation du verbe en pays tamoul (16 th -17 th centuries) by Inès Županov, in Archives des sciences sociales des religions (1998)

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• Grammar of the common dialect of the Tamul language , translated by George William Mahon (1848)

• A grammar of the high dialect of the Tamil language , termed Shen-Tamil , translated by Benjamin Babington (1822)

• An introduction to Tamil poetry

• Grammar of Old Tamil for students , by Eva Wilden (2018)

• Depictions of language and languages in early Tamil literature  : How Tamil became cool and straight , in Histoire, épistémologie, langage (2009)

• Reference grammar of classical Tamil poetry (150 bc - 6 th ad) by V. S. Rajam (1992)

• books about the Tamil language: Google books | Internet archive | Wikipedia

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• Depictions of language and languages in early Tamil literature : how Tamil became cool and straight , by Eva Wilden, in Histoire, épistémologie, langage (2009)

• Bilingual discourse and cross-cultural fertilisation : Sanskrit and Tamil in medieval India , edited by Whitney Cox & Vincenzo Vergiani (2013)

• Early Tamil poetics between Nāṭyaśāstra and Rāgamālā by Herman Tieken

• Praising the king in Tamil during the Pallava period by Emmanuel Francis

• Words for worship : Tamil and Sanskrit in medieval temple inscriptions , by Leslie Orr

• Studies in Tamil literature and history by Ramachandra Dikshitar (1936)

• Tamil studies , or Essays on the history of the Tamil people, language, religion and literature , by Srinivasa Aiyangar (1914)

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• Traduire le Tēvāram ou la bosse du roi pāṇḍya , by Uthaya Veluppillai, in Bulletin d'Études indiennes (2015)

• L'hospitalité dans le Periyapurāṇam  : au service des serviteurs (2003)

• Le Tiruppāvaḷ d'Āṇṭāḷ  : un texte tamoul de dévotion vishnouite , with translation into French & notes by Jean Filliozat (1972)

• The Naladiyār : classical Tamil, with introduction, translation & lexicon, by George Uglow Pope (1893)

• The "Sacred" Kurral of Tiruvalluva-Nāyanār : Tamil text, with translation, notes & lexicon (1886)

• Hero stone inscriptions in Tamil (450-650) by Appasamy Murugaiyan, in New dimensions in Tamil epigraphy (2012)

• Stèles funéraires en pays tamoul (2012)

• BibleGateway : Bible en Tamil, Easy to read version

• The Gospel of Luke , English & Tamil (1895)

• The New Testament in Tamil (1859)

• The Gospel according to St. Matthew in Tamil (1841)

• Book of Psalms in Tamil (1849) (Latin script, phonetic)

• Protestant translations of the Bible (1714-1995) and defining a Protestant Tamil identity , by Hephzibah Israel, thesis (2004)

மனிதப் பிறிவியினர் சகலரும் சுதந்திரமாகவே பிறக்கின்றனர் அவர்கள் மதிப்பிலும், உரிமைகளிலும் சமமானவர்கள், அவர்கள் நியாயத்தையும் மனச்சாட்சியையும் இயற்பண்பாகப் பெற்றவர்கள். அவர்கள் ஒருவருடனொருவர் சகோதர உணர்வுப் பாங்கில் நடந்துகொள்ளல் வேண்டும்.

• Universal Declaration of Human Rights : translation into Tamil (+ audio)

→ First article in different languages

→ Universal Declaration of Human Rights : bilingual text, in Tamil, English & other languages

• Imperial languages and public writings in Tamil South India : a bird's eye view in the very longue durée , by Emmanuel Francis, in Primary sources and Asian pasts (2021)

• Les « rois anciens » du pays tamoul by Charlotte Schmid, in Bulletin de l'École française d'Extrême-Orient (2020)

• Au seuil du monde divin  : reflets et passages du dieu d' Ālantuṟai à Puḷḷamaṅkai (2005)

• Cīkāli : hymnes, héros, histoire  : rayonnement d'un lieu saint shivaïte au pays tamoul , by Uthaya Veluppillai, thesis (2013)

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ENGLISH TO TAMIL MACHINE TRANSLATION SYSTEM

2019, Language in India www.languageinindia.com ISSN 1930-2940 Vol. 19:5

This research material entitled “ENGLISH TO TAMIL MACHINE TRANSLATION SYSTEM USING PARALLEL CORPUS” was lying in my lap since 2013. I was planning to edit and publish it in book form after making necessary modifications. But as I have taken up some academic responsibility in Amrita University, Coimbatore after my retirement from Tamil University, I could not find time to fulfil my mission. So I am presenting it in raw format here. Let it see the light. Kindly bear with me. I am helpless. Statistical machine translation (SMT) is a machine translation paradigm where translations are generated on the basis of statistical models whose parameters are derived from the analysis of bilingual text corpora. The statistical approach contrasts with the rule-based approaches to machine translation as well as with example-based machine translation. Statistical machine translation (SMT) learns how to translate by analyzing existing human translations (known as bilingual text corpora). In contrast to the Rules Based Machine Translation (RBMT) approach that is usually word based, most mondern SMT systems are phrased based and assemble translations using overlap phrases. In phrase-based translation, the aim is to reduce the restrictions of word-based translation by translating whole sequences of words, where the lengths may differ. The sequences of words are called phrases, but typically are not linguistic phrases, but phrases found using statistical methods from bilingual text corpora. Analysis of bilingual text corpora (source and target languages) and monolingual corpora (target language) generates statistical models that transform text from one language to another with that statistical weights are used to decide the most likely translation.

Related Papers

Rajendran S

Tamil has initiated its technological development well in advance. It has made use of all the opportunities given to it for making it suitable for digitalization and computerization. The references listed below stand to establish its efforts in fulfilling the need of the day i.e. technological development. Governments, both state and central, funded liberally for the technological development of Tamil. This helped it to develop MT systems, wordNet and other NLP systems. Private organizations also contributed for this mission. Many individuals, both from inside and abroad, literally worked for Tamil computing. The organizations such as CIIL, AUKBCRC, Anna University, Amrita University, Tamil Virtual Academy, Tamil University, and Madras University need to appreciated for their efforts in uplifting Tamil in the era of Information Technology. Tamil has switched over to Unicode abandoning other systems. Tamil has comparatively commendable resouces and tools for NLP applications. Sumptuous amount of text corpora, speech corpora and parallel corpoara are available for Tamil. A good number of speech recognition systems and text to speech systems are developed for Tamil. Reliable morphological analyzers, morphological generators, syntactic parsers, chunkers, shallow parsers, named entiry recogniztion sytems optical character recognition system are available for Tamil. Computational semantics also improved in Tamil. There are attempts to develop word sense disambiguation system, question answering system, relationship extraction system, sentiment analysis systems, automatic summarization systems, and coreference resolution systems. Efforts are made to develop text generation systems too for Tamil. Tamil shows only positive symptoms in the technological development.

Tamil Visual Onto-thesaurus (TVOT or simply VOT) is an outcome of an extensive research activity that went on in the field of lexical semantics of Tamil. It went through several stages before being culminated into Tamil visual onto-thesaurus. It depicts our travel from Tamil thesaurus to Tamil word net. It is a lexical resource which amalgamates all sorts of information available in a dictionary, thesaurus and wordNet. The Dravidian wordNets (in which Tamil wordNet is one of the four components) built under the IndoWordNet project depended on an ontology developed by Western conceptualization of the world found in English). This has not taken into consideration the Indian conceptualization of the world depicted in the nikhandu tradition. Say for examples, nikhandus have classifications such a six types of tastes, nine types of planets (gragams), 7 types of mandalams (a type of division), 15 tidis (15 phases of moon), etc. which are crucial for Indian tradition. In the western oriented WordNet ontology there is no scope for the visualization of concepts depicted in nikhandus. Moreover building a wordNet based on Hindi wordNet which in turn is built on English wordNet will take many years to complete and it would miss the conceptualization depicted in Indian tradition. Apart from this the extension approach of building Tamil wordNet using Hindi wordNet cannot fulfill Dravidian conceptualization. A merger approach of building separate wordNets and collapsing them into one would have been a preferable approach. The present visual onto-thesaurus is based on the Indian and Dravidian conceptualization and the process of building one is comparatively very simple. We have the plan to mend it into a generic one so that all the Dravidian languages can be easily accommodated into it.

Dr. Pitambar Behera

This research work presents a probability-based CRF++ parts of speech (POS) tagger for Odia language. A corpus of approximately 600k tokens has been annotated manually in the Indian Languages Corpora Initiative (ILCI) project for Odia. The whole Odia corpus has been annotated based on the Bureau of Indian Standards (BIS) tagset developed by the DIT, govt. of India with some modifications under the ILCI. The tagger has been trained and tested with 2, 36, 793 and 1, 28, 646 tokens respectively. It provides 94.39% accuracy in the domain of seen data and 88.87% in the unseen dataset in precision and recall measures. In addition, this study further conducts an IA (inter-annotator) agreement, an error analysis to figure out salient erroneous labels committed by the automatic tagger and provides various suggestions to improve its efficiency. Furthermore, this study also provides the user-interface architecture and its functionalities.

Rajendran Sankaravelayuthan

The use of computer for language analysis leads to the technological development of languages in general, and Tamil, in particular. The world scenario has its impact on Tamil language too. Both the government and private organizations have initiated programs for the technological development of Tamil language. The Department of Electronics had conducted training Courses on Natural Language Processing through selected institutions throughout India and paved way to technological development of Tamil. It funded Machine Translation programs among Indian languages and between English and Indian languages. It also funded for the development of corpus for Indian languages. It had identified certain centres for the Technological Development of Indian languages and funded them to initiate projects, which aims to achieve their goal Anna University at Chennai had been identified for the technological development of Tamil language and provided with a fund of a few crores of rupees to fulfill th...

Machine translation is the task of translating the text in source language to target language, automatically. Machine translation can be considered as an area of applied research that draws ideas and techniques from linguistics, computer science, artificial intelligence, translation theory, and statistics. Even though machine translation was envisioned as a computer application in the 1950‘s and research has been made for 60 years, machine translation is still considered to be an open problem. The demand for machine translation is growing rapidly. As multilingualism is considered to be a part of democracy, the European Union funds EuroMatrixPlus, a project to build machine translation system for all European language pairs, to automatically translate the documents to 23 official languages, which were being translated manually. Also as the United Nations is translating a large number of documents into several languages, the UN has created bilingual corpora for some language pairs like Chinese – English, Arabic–English which are among the largest bilingual corpora distributed through the Linguistic Data Consortium. In the World Wide Web, as around 20% of web pages and other resources are available in their national languages, machine translation can be used to translate these web pages and resources to the required language in order to understand the content in those pages and resources, thereby decreasing the effect of language as a barrier of communication. In a linguistically diverged country like India, machine translation is an important and most appropriate technology for localization. Human translation in India can be found since the ancient times which are being evident from the various works of philosophy, arts, mythology, religion and science which have been translated among ancient and modern Indian languages. Also, numerous classic works of art, ancient, medieval and modern, have also been translated between European and Indian languages since the 18th century. As of now, human translation in India finds application mainly in the administration, media and education, and to a lesser extent, in business, arts and science and technology. India has 22 constitutional languages, which were written in 10 different scripts. Hindi is the official language of the India. English is the language which is most widely used in the media, commerce, science and technology and education. Many of the states have their own regional language, which is either Hindi or one of the other constitutional languages. Only about 5% of the population speaks English. In such a situation, there is a big market for translation between English and the various Indian languages. Currently, the translation is done manually. Use of automation is largely restricted to word processing. Two specific examples of high volume manual translation are -translation of news from English into local languages, translation of annual reports of government departments and public sector units among, English, Hindi and the local language. Many resources such as news, weather reports, books, etc., in English are being manually translated to Indian languages. Of these, News and weather reports from all around the world are translated from English to Indian languages by human translators more often. Human translation is slow and also consumes more time and cost compared to machine translation. It is clear from this that there is large market available for machine translation rather than human translation from English into Indian languages. The reason for choosing automatic machine translation rather than human translation is that machine translation is better, faster and cheaper than human translation. Tamil, a Dravidian language spoken by around 72 million people is the official language of Tamil Nadu state government of India. Tamil in its eagerness to gather information from English resort to build English-Tamil machine translation systems. Many English-Tamil machine translation systems are getting built, but none could serve the ambitious need of Tamil. This work is intended pursue this work in a new perspective.

Language is burdened with ambiguity; a single utterance can have a number of interpretations or meanings. The native speakers who speak a natural language have an implicit knowledge or competence to understand correctly these ambiguous utterances. They are capable of assigning an interpretation to any of the utterances they generate. They not only assign an interpretation to every utterance in their language, but also know that there are utterances that may have more than one semantic interpretation. These utterances are usually referred to as ambiguous utterances. When an utterance has more than one interpretation, it is usually referred to as ambiguous. Ambiguity means that utterances have same form but have different interpretations. Ambiguity may result from two homonyms/homographs occurring in the same structural position, as in the following example.

Work on Malayalam WordNet was initiated in Amrita Vishvavidya Peetam, Coimbatore in December, 2011 as a part of the project entitled “Development of Dravidian WordNet: An Integrated WordNet for Telugu, Tamil, Kannada and Malayalam”, funded by Department of Information Technology, MCIT, Govt. of India. The main objective of the project is to build WordNets for Dravidian languages by making use of the already built Hindi WordNet under the project scheme IndowordNet. Hindi WordNet has been built based on Princeton English WordNet which is a component of EuroWordNet. The main objective of EuroWordNet is to develop an extensive and high quality of multilingual database with WordNets for several languages (mainly European Languages such as French, German, Czech, Italian, etc.) in a cost-effective manner. On similar line, IndowordNet is being built for Indian languages. Malayalam wordNet is a component of Dravidian wordNet which in turn is the component of IndowordNet. Malayalam wordNet is an online lexical database. It is useful for many applications of Natural Language Processing.

The use of computer for language analysis leads to the technological development of languages in general, and Tamil, in particular. The world scenario has its impact on Tamil language too. Both the government and private organizations have initiated programs for the technological development of Tamil language. The Department of Electronics had conducted training Courses on Natural Language Processing through selected institutions throughout India and paved way to technological development of Tamil. It funded Machine Translation programs among Indian languages and between English and Indian languages. It also funded for the development of corpus for Indian languages. It had identified certain centers for the Technological Development of Indian languages and funded them to initiate projects, which aims to achieve their goal. Anna University at Chennai had been identified for the technological development of Tamil language and provided with a fund of a few crores of rupees to fulfill his mission. Under this scheme a Resource Center for Indian Language Technology Solutions-Tamil has been established at Anna University. A team of researchers employed under the scheme has prepared a number of Language Technology Products. This has lead to the technological development of Tamil in many areas. Many other organizations, both government and private, followed this. Tamil University at Thanjavur, Tamil Virtual University, AUKBC Research Centre at Chennai, Central Institute of Indian languages at Mysore and International Forum for Information Technology in Tamil (INFITT), which conducts international conference of Tamil internet every year, put their efforts for the technological development of Tamil. Apart from the above institutions IIT, Chennai, IISC, Bangalore, and Micro Software, Bangalore also have contributed for the technological development of Tamil. In this paper the technological development of Tamil has been classified under certain heads nd the research works under taken and successfully completed as well as the products made are discussed in details.

Parsing is actually related to the automatic analysis of texts according to a grammar. Technically, it is used to refer to practice of assigning syntactic structure to a text. It is usually performed after basic morphosyntactic categories have been identified in a text. Based on different grammars parsing brings these morphosyntactic categories into higher-level syntactic relationships with one another. The survey of the state of art of parsing in Tamil reflects upon the global scenario. More or less the trends of the global arena in natural language processing are very much represented in Tamil too.

The concept of transfer grammar is not a recent phenomenon. Even in 1954 Harris discusses about the importance transfer grammar in the context of translation, machine translation, language teaching and language learning. We became aware of it recently due to our involvement in machine translation (MT). Presently we are interested in preparing a transfer grammar for English Tamil MT. Harris has proposed an elaborate methodology to prepare a transfer grammar (His idea of transfer grammar has been explained below under the heading “Transfer Grammar”. Here we narrow down our efforts just to correlate syntactic structure of English with that of Tamil from the point of view preparing a transfer grammar for English-Tamil machine translation. For this purpose the computable syntactic structures of English and Tamil have been worked out. These computational syntactic structure analyses are different form ordinary syntactic structure analyses in the sense that the computational syntactic structures are viable for computational processing. A transfer grammar for machine translation has to be prepared using these computational syntactic structure analyses. A transfer grammar is an important component in a machine translation system. This helps us to map one language structure into another language structure. As English and Tamil belongs to two different types of language groups, that is English as predominantly SVO patterned language and Tamil a predominantly SOV patterned language showing unique characteristics which differentiate them drastically from one another, it is possible to manipulate these differences to form transfer rules. These transfer rules can be used to map the English structure into Tamil Structure and vice versa.

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thesis in Tamil தமிழ்

• ஆய்வறிக்கை ⇄ thesis
• ஆராய்ச்சிக் கட்டுரை ⇄ thesis

thesis in Gujarati ગુજરાતી

• યુનિવર્સિટીની ઉપાધિ મેળ વવા માટે લખેલો પ્રબંધ. ⇄ thesis
• સમર્થન કે પુરવાર કરવાનો સિદ્ધાન્ત ⇄ thesis

thesis in Hindi हिन्दी

• थिसिस ⇄ thesis
• थीसिस ⇄ thesis
• निबंध ⇄ thesis
• प्रसंग ⇄ thesis
• मान्यता ⇄ thesis
• वचन ⇄ thesis
• वाद ⇄ thesis
• स्थापना ⇄ thesis

thesis in Kannada ಕನ್ನಡ

• ನಿಲವು ⇄ thesis
• ಪ್ರಬಮ್ಧ ⇄ thesis
• ಪ್ರೌಢ ಪ್ರಬಮ್ಧ ⇄ thesis

thesis in Maithili মৈথিলী

• शोध-प्रबन्ध ⇄ thesis

thesis in Marathi मराठी

• पक्ष ⇄ thesis
• प्रबंध ⇄ thesis
• स्थिति ⇄ thesis

thesis in Santali

• प्रबन्धः ⇄ thesis
• सिद्धान्त ⇄ thesis

thesis in Sindhi سنڌي

• مضمون، ڳالهه ⇄ Thesis

thesis in Telugu తెలుగు

• కోటి ⇄ thesis
• పక్షము ⇄ thesis
• వితర్కనీయ విషయము. వొకసంగతి చెప్పి దీని మిద మీకు తోచేదాన్ని వ్రాసుకొని రమ్మని పిల్లకాయలకు చెప్పినాడు. ⇄ thesis

thesis in Urdu اُردُو

• مسیلہ ⇄ thesis

thesis in English

• thesis ⇄ thesis, noun, pl.-ses. 1a. a proposition or statement to be proved or to be maintained against objections. b. a necessary preliminary assumption, whether to be proved or taken for granted; postulate. 2a. an essay. b. an essay or

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Thesis in tamil.

thesis | Tamil dictionary translates English to Tamil and Tamil to English thesis words      thesis phrases with thesis synonyms thesis antonyms    thesis pronunciations .

thesis meaning in Tamil

thesis in Tamil    Tamil of translation of thesis    Tamil meaning of thesis    what is thesis in Tamil    dictionary definition, antonym, and synonym of thesis

Thesaurus: Synonym & Antonym of thesis

Indian Official Languages Dictionary is significantly better than Google translation offers multiple meanings, alternate words list of thesis    thesis phrases    with similar meanings in Tamil தமிழ், Tamil தமிழ் dictionary    Tamil தமிழ் thesis translation    thesis meaning    thesis definition    thesis antonym    thesis synonym Tamil language reference work for finding synonyms,   antonyms of thesis .

This page is an online lexical resource, contains a list of the thesis like words    in a Tamil language in the order of the alphabets, and that tells you what they mean, in the same or other languages including English.

What is 'thesis' meaning in Tamil?

Input a term thesis by either copy & post, drag & drop, or simply by typing in the search box. meanings of thesis will be translated.

Indian Official Languages Dictionary - KHANDBAHALE.COM | भारतीय राजभाषा शब्दकोश - खांडबहाले.कॉम is a digital dictionary platform for 22 Official Languages of India with an extensive vocabulary of 10+ million words, meanings & definitions. The languages offered along with English are Assamese (অসমীয়া) Bengali (বাংলা) Bodo (बड़ो) Dogri (डोगरी) Gujarati (ગુજરાતી) Hindi (हिन्दी) Kannada (ಕನ್ನಡ) Kashmiri (कॉशुर) Konkani (कोंकणी) Maithili (মৈথিলী) Malayalam (മലയാളം) Manipuri (মৈতৈলোন্) Marathi (मराठी) Nepali (नेपाली) Oriya (ଓଡ଼ିଆ) Punjabi (ਪੰਜਾਬੀ) Sanskrit (संस्कृतम्) Santali (ᱥᱟᱱᱛᱟᱲᱤ) Sindhi (سنڌي) Tamil (தமிழ்) Telugu (తెలుగు) Urdu (اُردُو)

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