Machine Translation Approaches and Survey for Indian ... - aclclp

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68 Antony P. J.reordering the source (English) sentence as per target (Hindi) syntax, and (ii) using thesuffixes of target (Hindi) words.4.36 Prototype MT System from Text-To-Indian Sign Language (ISL)This is a very different approach to MT that is intended for dissemination of information to thedeaf people in India and was proposed by Tirthankar Dasgupta, Sandipan Dandpat, andAnupam Basu (Dasgupta et al. 2008; Harshawardhan et al., 2011). At present, a prototypeversion of English to Indian Sign Language has been developed and the ISL syntax isrepresented based on Lexical Functional Grammar (LFG) formalism.4.37 An Adaptable Frame based system for Dravidian language Processing(1999)In the proposed work, a different approach that makes use of the karaka relations for sentencecomprehension is used in the frame-based translation system for Dravidian languages (Idiculaet al., 1999). Two pattern-directed application-oriented experiments are conducted, and thesame meaning representation technique is used in both cases. In the first experiment,translation is done from a free word order language to fixed word order one, where both thesource and destination are natural languages. In the second experiment, however, the TL is anartificial language with a rigid syntax. Even though there is a difference in the generation ofthe target sentence, the results obtained in both experiments are encouraging.4.38 English-Telugu T2T MT and Telugu-Tamil MT System (2004)CALTS in collaboration with IIIT, Hyderabad; Telugu University, Hyderabad; and OsmaniaUniversity, Hyderabad developed an English-Telugu and Telugu-Tamil MT system under thesupervision of Prof. Rajeev Sangal (CALTS). The English-Telugu system uses anEnglish-Telugu machine aided translation lexicon of size 42000 words and a wordformsynthesizer for Telugu. The Telugu-Tamil MT system was developed based on the availableresources at CALTS: Telugu Morphological analyzer, Tamil generator, verb sensedisambiguator, and Telugu-Tamil machine aided translation dictionary. The performance ofthe systems is encouraging, and it handles source sentences of varying complexity.4.39 Developing English-Urdu MT Via Hindi (2009)R. Mahesh K. Sinha proposed a different strategy for deriving English to Urdu translationusing an English to Hindi MT system (R. Mahesh et al., 2009). In the proposed method, anEnglish-Hindi lexical database is used to collect all possible Hindi words and phrases. Thesewords and phrases are further augmented by including their morphological variations andattaching all possible postpositions. Urdu is structurally very close to Hindi and this
Machine Translation Approaches and Survey for Indian Languages 69augmented list is used to provide mapping from Hindi to Urdu. The advantage of thistranslation system is that the grammatical analysis of English provides all the necessaryinformation needed for Hindi to Urdu mapping and no part of speech tagging, chunking, orparsing of Hindi has been used for translation.4.40 Bengali-Assamese automatic MT system-VAASAANUBAADA (2002)Kommaluri Vijayanand, S. Choudhury and Pranab Ratna proposed an automatic bilingual MTfor Bengali to Assamese using an example-based approach (Kommaluri et al., 2002). Theyused a manually created aligned bilingual corpus by feeding real examples using pseudo code.The quality of the translation was improved by preprocessing the longer input sentences andalso via the backtracking techniques. Since the grammatical structure of Bengali andAssamese is very similar, lexical word groups are required.4.41 Phrase based English-Tamil Translation System by Concept Labelingusing Translation Memory (2011)The Computational Engineering and Networking research centre of Amrita School ofEngineering, Coimbatore, proposed an English-Tamil translation system. The system is set ona phrase-based approach by incorporating concept labeling using translation memory ofparallel corpora (Harshawardhan et al., 2011). The translation system consists of 50,000English-Tamil parallel sentences, 5000 proverbs, and 1000 idioms and phrases, with adictionary containing more than 2,00,000 technical words and 100,000 general words. Thesystem has an accuracy of 70%.4.42 Rule-based Sentence Simplification for English to Tamil MT System(2011)This work is aimed at improving the translation quality of an MT system by simplifying thecomplex input sentences for an English to Tamil MT system (Poornima et al., 2011). In orderto simplify the complex sentences based on connectives, like relative pronouns orcoordinating and subordinating conjunctions, a rule-based technique is proposed. In thisapproach, a complex sentence is expressed as a list of sub-sentences while the meaningremains unaltered. The simplification task can be used as a preprocessing tool for MT wherethe initial splitting is based on delimiters and the simplification is based on connectives.4.43 Manipuri-English Bidirectional SMT Systems (2010)Using morphology and dependency relations, a Manipuri to English bidirectional SMT systemwas developed by Thoudam Doren Singh and Sivaji Bandyopadhyay (Doren Singh et al.,2010). The system uses a domain-specific parallel corpus of 10350 sentences from news for
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